Source Code for Module test_suite.system_tests.relax_disp

   1  ############################################################################### 
   2  #                                                                             # 
   3  # Copyright (C) 2006-2015 Edward d'Auvergne                                   # 
   4  # Copyright (C) 2009 Sebastien Morin                                          # 
   5  # Copyright (C) 2013-2014 Troels E. Linnet                                    # 
   6  #                                                                             # 
   7  # This file is part of the program relax (http://www.nmr-relax.com).          # 
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  22  ############################################################################### 
  23   
  24  # Python module imports. 
  25  from os import F_OK, access, getcwd, path, sep 
  26  import copy 
  27  from numpy import array, asarray, average, exp, median, inf, isnan, linspace, log, std, sum, zeros 
  28  from minfx.generic import generic_minimise 
  29  from random import gauss 
  30  import re, math 
  31  from tempfile import mkdtemp, NamedTemporaryFile 
  32   
  33   
  34  # relax module imports. 
  35  from auto_analyses import relax_disp 
  36  from auto_analyses.relax_disp_repeat_cpmg import DIC_KEY_FORMAT, Relax_disp_rep 
  37  from data_store import Relax_data_store; ds = Relax_data_store() 
  38  import dep_check 
  39  from lib.dispersion.variables import EXP_TYPE_CPMG_DQ, EXP_TYPE_CPMG_MQ, EXP_TYPE_CPMG_PROTON_MQ, EXP_TYPE_CPMG_PROTON_SQ, EXP_TYPE_CPMG_SQ, EXP_TYPE_CPMG_ZQ, EXP_TYPE_LIST, EXP_TYPE_R1RHO, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94, MODEL_IT99, MODEL_LIST_FULL, MODEL_LM63, MODEL_M61, MODEL_M61B, MODEL_MP05, MODEL_NOREX, MODEL_NS_CPMG_2SITE_3D_FULL, MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_R1RHO_2SITE, MODEL_PARAMS, MODEL_R2EFF, MODEL_TP02, MODEL_TAP03 
  40  from lib.errors import RelaxError 
  41  from lib.io import extract_data, get_file_path 
  42  from lib.spectrum.nmrpipe import show_apod_extract, show_apod_rmsd, show_apod_rmsd_dir_to_files, show_apod_rmsd_to_file 
  43  from pipe_control.mol_res_spin import generate_spin_string, return_spin, spin_loop 
  44  from pipe_control.minimise import assemble_scaling_matrix 
  45  from specific_analyses.relax_disp.checks import check_missing_r1 
  46  from specific_analyses.relax_disp.estimate_r2eff import estimate_r2eff 
  47  from specific_analyses.relax_disp.data import average_intensity, check_intensity_errors, generate_r20_key, get_curve_type, has_exponential_exp_type, loop_exp_frq, loop_exp_frq_offset_point, loop_time, return_grace_file_name_ini, return_param_key_from_data, spin_ids_to_containers 
  48  from specific_analyses.relax_disp.data import INTERPOLATE_DISP, INTERPOLATE_OFFSET, X_AXIS_DISP, X_AXIS_W_EFF, X_AXIS_THETA, Y_AXIS_R2_R1RHO, Y_AXIS_R2_EFF 
  49  from specific_analyses.relax_disp.model import models_info, nesting_param 
  50  from specific_analyses.relax_disp.parameters import linear_constraints 
  51  from status import Status; status = Status() 
  52  from target_functions.relax_fit_wrapper import Relax_fit_opt 
  53  from test_suite.system_tests.base_classes import SystemTestCase 
  54   
  55   
  56 -class Relax_disp(SystemTestCase): 
  57      """Class for testing various aspects specific to relaxation dispersion curve-fitting.""" 
  58   
  59 -    def __init__(self, methodName='runTest'): 
  60          """Skip certain tests if the C modules are non-functional. 
  61   
  62          @keyword methodName:    The name of the test. 
  63          @type methodName:       str 
  64          """ 
  65   
  66          # Execute the base class method. 
  67          super(Relax_disp, self).__init__(methodName) 
  68   
  69          # Tests to skip. 
  70          blacklist = [ 
  71              'test_m61b_data_to_m61b' 
  72          ] 
  73          if methodName in blacklist: 
  74              status.skipped_tests.append([methodName, None, self._skip_type]) 
  75   
  76          # Missing module. 
  77          if not dep_check.C_module_exp_fn: 
  78              # The list of tests to skip. 
  79              to_skip = [ 
  80                  "test_bug_atul_srivastava", 
  81                  "test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp", 
  82                  "test_bug_9999_slow_r1rho_r2eff_error_with_mc", 
  83                  "test_estimate_r2eff_err", 
  84                  "test_estimate_r2eff_err_auto", 
  85                  "test_estimate_r2eff_err_methods", 
  86                  "test_finite_value", 
  87                  "test_exp_fit", 
  88                  "test_m61_exp_data_to_m61", 
  89                  "test_r1rho_kjaergaard_auto", 
  90                  "test_r1rho_kjaergaard_auto_check_graphs", 
  91                  "test_r1rho_kjaergaard_man", 
  92                  "test_r1rho_kjaergaard_missing_r1", 
  93                  "test_value_write_calc_rotating_frame_params_auto_analysis" 
  94              ] 
  95   
  96              # Store in the status object. 
  97              if methodName in to_skip: 
  98                  status.skipped_tests.append([methodName, 'Relax curve-fitting C module', self._skip_type]) 
  99   
 100          # If not scipy.optimize.leastsq. 
 101          if not dep_check.scipy_module: 
 102              # The list of tests to skip. 
 103              to_skip = [ 
 104                  "test_estimate_r2eff_err_methods" 
 105              ] 
 106   
 107              # Store in the status object. 
 108              if methodName in to_skip: 
 109                  status.skipped_tests.append([methodName, 'scipy.optimize.leastsq module', self._skip_type]) 
 110   
 111          # If not NMRPipe showApod program in PATH. 
 112          if not dep_check.showApod_software: 
 113              # The list of tests to skip. 
 114              to_skip = [ 
 115                  "test_show_apod_extract", 
 116                  "test_show_apod_rmsd", 
 117                  "test_show_apod_rmsd_to_file", 
 118                  "test_show_apod_rmsd_dir_to_files" 
 119              ] 
 120   
 121              # Store in the status object. 
 122              if methodName in to_skip: 
 123                  status.skipped_tests.append([methodName, 'NMRPipe showApod program', self._skip_type]) 
 124   
 125          # If not matplotlib module 
 126          if not dep_check.matplotlib_module: 
 127              # The list of tests to skip. 
 128              to_skip = [ 
 129                  "test_repeat_cpmg" 
 130              ] 
 131   
 132              # Store in the status object. 
 133              if methodName in to_skip: 
 134                  status.skipped_tests.append([methodName, 'matplotlib module', self._skip_type]) 
 135   
 136   
 137 -    def setUp(self): 
 138          """Set up for all the functional tests.""" 
 139   
 140          # Create the data pipe. 
 141          self.interpreter.pipe.create('relax_disp', 'relax_disp') 
 142   
 143          # Create a temporary directory for dumping files. 
 144          ds.tmpdir = mkdtemp() 
 145          self.tmpdir = ds.tmpdir 
 146   
 147   
 148 -    def setup_bug_22146_unpacking_r2a_r2b_cluster(self, folder=None, model_analyse=None, places = 7): 
 149          """Setup data for the catch of U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered full dispersion models. 
 150   
 151          @keyword folder:            The name of the folder for the test data. 
 152          @type folder:               str 
 153          @keyword model_analyse:     The name of the model which will be tested. 
 154          @type model_analyse:        str 
 155          """ 
 156   
 157          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
 158   
 159          # Data. 
 160          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_22146_unpacking_r2a_r2b_cluster'+sep+folder 
 161   
 162          ## Experiments 
 163          # Exp 1 
 164          sfrq_1 = 500.0*1E6 
 165          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
 166          time_T2_1 = 0.05 
 167          ncycs_1 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 40, 50] 
 168          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 169          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 170          r2eff_errs_1 = [0.0] * len(ncycs_1) 
 171          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
 172   
 173          sfrq_2 = 600.0*1E6 
 174          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
 175          time_T2_2 = 0.06 
 176          ncycs_2 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 40, 60] 
 177          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 178          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 179          r2eff_errs_2 = [0.0] * len(ncycs_2) 
 180          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
 181   
 182          sfrq_3 = 700.0*1E6 
 183          r20_key_3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_3) 
 184          time_T2_3 = 0.07 
 185          ncycs_3 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 50, 70] 
 186          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 187          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 188          r2eff_errs_3 = [0.0] * len(ncycs_3) 
 189          exp_3 = [sfrq_3, time_T2_3, ncycs_3, r2eff_errs_3] 
 190   
 191          # Collect all exps 
 192          exps = [exp_1, exp_2, exp_3] 
 193   
 194          R20 = [5.1, 5.2, 5.3, 10.1, 10.2, 10.3, 6.1, 6.2, 6.3, 11.1, 11.2, 11.3, 7.1, 7.2, 7.3, 12.1, 12.2, 12.3, 8.1, 8.2, 8.3, 13.1, 13.2, 13.3] 
 195          dw_arr = [1.0, 2.0, 3.0, 4.0] 
 196          pA_arr = [0.9] 
 197          kex_arr = [1000.] 
 198   
 199          spins = [ 
 200                  ['Ala', 1, 'N', {'r2a': {r20_key_1: R20[0], r20_key_2: R20[1], r20_key_3: R20[2]}, 'r2b': {r20_key_1: R20[3], r20_key_2: R20[4], r20_key_3: R20[5]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[0]}], 
 201                  ['Ala', 2, 'N', {'r2a': {r20_key_1: R20[6], r20_key_2: R20[7], r20_key_3: R20[8]}, 'r2b': {r20_key_1: R20[9], r20_key_2: R20[10], r20_key_3: R20[11]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[1]}], 
 202                  ['Ala', 3, 'N', {'r2a': {r20_key_1: R20[12], r20_key_2: R20[13], r20_key_3: R20[14]}, 'r2b': {r20_key_1: R20[15], r20_key_2: R20[16], r20_key_3: R20[17]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[2]}], 
 203                  ['Ala', 4, 'N', {'r2a': {r20_key_1: R20[18], r20_key_2: R20[19], r20_key_3: R20[20]}, 'r2b': {r20_key_1: R20[21], r20_key_2: R20[22], r20_key_3: R20[23]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[3]}], 
 204                  ] 
 205   
 206          # Create the data pipe. 
 207          pipe_name = 'base pipe' 
 208          pipe_type = 'relax_disp' 
 209          pipe_bundle = 'relax_disp' 
 210          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type, bundle = pipe_bundle) 
 211   
 212          # Generate the sequence. 
 213          for res_name, res_num, spin_name, params in spins: 
 214              self.interpreter.spin.create(res_name=res_name, res_num=res_num, spin_name=spin_name) 
 215   
 216          # Set isotope 
 217          self.interpreter.spin.isotope('15N', spin_id='@N') 
 218   
 219          # Now loop over the experiments, to set the variables in relax. 
 220          exp_ids = [] 
 221          for exp_i in exps: 
 222              sfrq, time_T2, ncycs, r2eff_errs = exp_i 
 223              exp_id = 'CPMG_%3.1f' % (sfrq/1E6) 
 224              exp_ids.append(exp_id) 
 225   
 226              ids = [] 
 227              for ncyc in ncycs: 
 228                  nu_cpmg = ncyc / time_T2 
 229                  cur_id = '%s_%.1f' % (exp_id, nu_cpmg) 
 230                  ids.append(cur_id) 
 231   
 232                  # Set the spectrometer frequency. 
 233                  self.interpreter.spectrometer.frequency(id=cur_id, frq=sfrq) 
 234   
 235                  # Set the experiment type. 
 236                  self.interpreter.relax_disp.exp_type(spectrum_id=cur_id, exp_type=EXP_TYPE_CPMG_SQ) 
 237   
 238                  # Set the relaxation dispersion CPMG constant time delay T (in s). 
 239                  self.interpreter.relax_disp.relax_time(spectrum_id=cur_id, time=time_T2) 
 240   
 241                  # Set the relaxation dispersion CPMG frequencies. 
 242                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=cur_id, cpmg_frq=nu_cpmg) 
 243   
 244          print("\n\nThe experiment IDs are %s." % cdp.spectrum_ids) 
 245   
 246          ### Now do fitting. 
 247          # Change pipe. 
 248   
 249          pipe_name_MODEL = "%s_%s"%(pipe_name, model_analyse) 
 250          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_MODEL, bundle_to = pipe_bundle) 
 251          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
 252   
 253          # Now read data in. 
 254          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
 255              exp_id = exp_ids[mi] 
 256              exp_i = exps[mi] 
 257              sfrq, time_T2, ncycs, r2eff_errs = exp_i 
 258   
 259              # Then loop over the spins. 
 260              for res_name, res_num, spin_name, params in spins: 
 261                  cur_spin_id = ":%i@%s"%(res_num, spin_name) 
 262   
 263                  # Define file name 
 264                  file_name = "%s%s.txt" % (exp_id, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) 
 265   
 266                  # Read in the R2eff file to put into spin structure. 
 267                  self.interpreter.relax_disp.r2eff_read_spin(id=exp_id, spin_id=cur_spin_id, file=file_name, dir=data_path, disp_point_col=1, data_col=2, error_col=3) 
 268   
 269          # Then select model. 
 270          self.interpreter.relax_disp.select_model(model=model_analyse) 
 271   
 272          # Then cluster 
 273          self.interpreter.relax_disp.cluster('model_cluster', ":1-100") 
 274   
 275          # Grid search 
 276          low_arr = R20 + dw_arr + pA_arr + kex_arr 
 277          self.interpreter.minimise.grid_search(lower=low_arr, upper=low_arr, inc=1, constraints=True, verbosity=1) 
 278   
 279          # Then loop over the defined spins and read the parameters. 
 280          for i in range(len(spins)): 
 281              res_name, res_num, spin_name, params = spins[i] 
 282              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
 283              cur_spin = return_spin(cur_spin_id) 
 284   
 285              for mo_param in cur_spin.params: 
 286                  print(mo_param) 
 287                  # The R2 is a dictionary, depending on spectrometer frequency. 
 288                  if isinstance(getattr(cur_spin, mo_param), dict): 
 289                      for key, val in list(getattr(cur_spin, mo_param).items()): 
 290                          should_be = params[mo_param][key] 
 291                          print(cur_spin.model, res_name, cur_spin_id, mo_param, key, float(val), should_be) 
 292                          self.assertAlmostEqual(val, should_be) 
 293                  else: 
 294                      should_be = float(params[mo_param]) 
 295                      val = getattr(cur_spin, mo_param) 
 296                      print(cur_spin.model, res_name, cur_spin_id, mo_param, val, should_be) 
 297                      self.assertAlmostEqual(val, should_be) 
 298   
 299              # Test chi2. 
 300              # At this point the chi-squared value at the solution should be zero, as the relaxation data was created with the same parameter values. 
 301              self.assertAlmostEqual(cur_spin.chi2, 0.0, places = places) 
 302   
 303   
 304 -    def setup_r1rho_kjaergaard(self, cluster_ids=[], read_R1=True): 
 305          """Set up the data for the test_r1rho_kjaergaard_*() system tests.""" 
 306   
 307          # The path to the data files. 
 308          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
 309   
 310          # Set pipe name, bundle and type. 
 311          ds.pipe_name = 'base pipe' 
 312          ds.pipe_bundle = 'relax_disp' 
 313          ds.pipe_type = 'relax_disp' 
 314   
 315          # Create the data pipe. 
 316          self.interpreter.pipe.create(pipe_name=ds.pipe_name, bundle=ds.pipe_bundle, pipe_type=ds.pipe_type) 
 317   
 318          # Read the spins. 
 319          self.interpreter.spectrum.read_spins(file='1_0_46_0_max_standard.ser', dir=data_path+sep+'peak_lists') 
 320   
 321          # Name the isotope for field strength scaling. 
 322          self.interpreter.spin.isotope(isotope='15N') 
 323   
 324          # Set number of experiments to be used. 
 325          NR_exp = 70 
 326   
 327          # Load the experiments settings file. 
 328          expfile = open(data_path+sep+'exp_parameters_sort.txt', 'r') 
 329          expfileslines = expfile.readlines()[:NR_exp] 
 330          expfile.close() 
 331   
 332          # In MHz 
 333          yOBS = 81.050 
 334          # In ppm 
 335          yCAR = 118.078 
 336          centerPPM_N15 = yCAR 
 337   
 338          ## Read the chemical shift data. 
 339          self.interpreter.chemical_shift.read(file='1_0_46_0_max_standard.ser', dir=data_path+sep+'peak_lists') 
 340   
 341          # The lock power to field, has been found in an calibration experiment. 
 342          spin_lock_field_strengths_Hz = {'35': 431.0, '39': 651.2, '41': 800.5, '43': 984.0, '46': 1341.11, '48': 1648.5} 
 343   
 344          # Apply spectra settings. 
 345          # Count settings 
 346          j = 0 
 347          for i in range(len(expfileslines)): 
 348              line = expfileslines[i] 
 349              if line[0] == "#": 
 350                  continue 
 351              else: 
 352                  # DIRN I deltadof2 dpwr2slock ncyc trim ss sfrq 
 353                  DIRN = line.split()[0] 
 354                  I = int(line.split()[1]) 
 355                  deltadof2 = line.split()[2] 
 356                  dpwr2slock = line.split()[3] 
 357                  ncyc = int(line.split()[4]) 
 358                  trim = float(line.split()[5]) 
 359                  ss = int(line.split()[6]) 
 360                  set_sfrq = float(line.split()[7]) 
 361                  apod_rmsd = float(line.split()[8]) 
 362                  spin_lock_field_strength = spin_lock_field_strengths_Hz[dpwr2slock] 
 363   
 364                  # Calculate spin_lock time 
 365                  time_sl = 2*ncyc*trim 
 366   
 367                  # Define file name for peak list. 
 368                  FNAME = "%s_%s_%s_%s_max_standard.ser"%(I, deltadof2, dpwr2slock, ncyc) 
 369                  sp_id = "%s_%s_%s_%s"%(I, deltadof2, dpwr2slock, ncyc) 
 370   
 371                  # Load the peak intensities. 
 372                  self.interpreter.spectrum.read_intensities(file=FNAME, dir=data_path+sep+'peak_lists', spectrum_id=sp_id, int_method='height') 
 373   
 374                  # Set the peak intensity errors, as defined as the baseplane RMSD. 
 375                  self.interpreter.spectrum.baseplane_rmsd(error=apod_rmsd, spectrum_id=sp_id) 
 376   
 377                  # Set the relaxation dispersion experiment type. 
 378                  self.interpreter.relax_disp.exp_type(spectrum_id=sp_id, exp_type='R1rho') 
 379   
 380                  # Set The spin-lock field strength, nu1, in Hz 
 381                  self.interpreter.relax_disp.spin_lock_field(spectrum_id=sp_id, field=spin_lock_field_strength) 
 382   
 383                  # Calculating the spin-lock offset in ppm, from offsets values provided in Hz. 
 384                  frq_N15_Hz = yOBS * 1E6 
 385                  offset_ppm_N15 = float(deltadof2) / frq_N15_Hz * 1E6 
 386                  omega_rf_ppm = centerPPM_N15 + offset_ppm_N15 
 387   
 388                  # Set The spin-lock offset, omega_rf, in ppm. 
 389                  self.interpreter.relax_disp.spin_lock_offset(spectrum_id=sp_id, offset=omega_rf_ppm) 
 390   
 391                  # Set the relaxation times (in s). 
 392                  self.interpreter.relax_disp.relax_time(spectrum_id=sp_id, time=time_sl) 
 393   
 394                  # Set the spectrometer frequency. 
 395                  self.interpreter.spectrometer.frequency(id=sp_id, frq=set_sfrq, units='MHz') 
 396   
 397                  # Add to counter 
 398                  j += 1 
 399   
 400   
 401          print("Testing the number of settings") 
 402          print("Number of settings iterations is: %s. Number of cdp.exp_type is: %s"%(i, len(cdp.exp_type))) 
 403          self.assertEqual(70, len(expfileslines)) 
 404          self.assertEqual(69, j) 
 405          self.assertEqual(69, len(cdp.exp_type)) 
 406   
 407          # Cluster spins 
 408          for curspin in cluster_ids: 
 409              print("Adding spin %s to cluster"%curspin) 
 410              self.interpreter.relax_disp.cluster('model_cluster', curspin) 
 411   
 412          # De-select for analysis those spins who have not been clustered 
 413          for free_spin in cdp.clustering['free spins']: 
 414              print("Deselecting free spin %s"%free_spin) 
 415              self.interpreter.deselect.spin(spin_id=free_spin, change_all=False) 
 416   
 417   
 418          #Paper         reference values 
 419          #              Resi   Resn         R1_rad_s   R1err_rad_s   R2_rad_s   R2err_rad_s   kEX_rad_s      kEXerr_rad_s  phi_rad2_s2     phierr_rad2_s2    phi_ppm2         phierr_ppm2 
 420          # Scaling rad2_s2 to ppm2: scaling_rad2_s2 = frequency_to_ppm(frq=1/(2*pi), B0=cdp.spectrometer_frq_list[0], isotope='15N')**2 = 3.85167990165e-06 
 421          ds.ref = dict() 
 422          ds.ref[':13@N'] = [13,   'L13N-HN',   1.32394,   0.14687,      8.16007,   1.01237,      13193.82986,   2307.09152,   58703.06446,    22413.09854,      0.2261054135,    0.0863280812] 
 423          ds.ref[':15@N'] = [15,   'R15N-HN',   1.34428,   0.14056,      7.83256,   0.67559,      13193.82986,   2307.09152,   28688.33492,    13480.72253,      0.110498283,     0.051923428] 
 424          ds.ref[':16@N'] = [16,   'T16N-HN',   1.71514,   0.13651,      17.44216,  0.98583,      13193.82986,   2307.09152,   57356.77617,    21892.44205,      0.220919942,     0.084322679] 
 425          ds.ref[':25@N'] = [25,   'Q25N-HN',   1.82412,   0.15809,      9.09447,   2.09215,      13193.82986,   2307.09152,   143111.13431,   49535.80302,      0.5512182797,    0.1907960569] 
 426          ds.ref[':26@N'] = [26,   'Q26N-HN',   1.45746,   0.14127,      10.22801,  0.67116,      13193.82986,   2307.09152,   28187.06876,    13359.01615,      0.1085675662,    0.051454654] 
 427          ds.ref[':28@N'] = [28,   'Q28N-HN',   1.48095,   0.14231,      10.33552,  0.691,        13193.82986,   2307.09152,   30088.0686,     13920.25654,      0.1158896091,    0.0536163723] 
 428          ds.ref[':39@N'] = [39,   'L39N-HN',   1.46094,   0.14514,      8.02194,   0.84649,      13193.82986,   2307.09152,   44130.18538,    18104.55064,      0.1699753481,    0.0697329338] 
 429          ds.ref[':40@N'] = [40,   'M40N-HN',   1.21381,   0.14035,      12.19112,  0.81418,      13193.82986,   2307.09152,   41834.90493,    17319.92156,      0.1611346625,    0.0667107938] 
 430          ds.ref[':41@N'] = [41,   'A41N-HN',   1.29296,   0.14286,      9.29941,   0.66246,      13193.82986,   2307.09152,   26694.8921,     13080.66782,      0.1028201794,    0.0503825453] 
 431          ds.ref[':43@N'] = [43,   'F43N-HN',   1.33626,   0.14352,      12.73816,  1.17386,      13193.82986,   2307.09152,   70347.63797,    26648.30524,      0.2709565833,    0.1026407417] 
 432          ds.ref[':44@N'] = [44,   'I44N-HN',   1.28487,   0.1462,       12.70158,  1.52079,      13193.82986,   2307.09152,   95616.20461,    35307.79817,      0.3682830136,    0.1359943366] 
 433          ds.ref[':45@N'] = [45,   'K45N-HN',   1.59227,   0.14591,      9.54457,   0.95596,      13193.82986,   2307.09152,   53849.7826,     21009.89973,      0.2074121253,    0.0809234085] 
 434          ds.ref[':49@N'] = [49,   'A49N-HN',   1.38521,   0.14148,      4.44842,   0.88647,      13193.82986,   2307.09152,   40686.65286,    18501.20774,      0.1567119631,    0.07126073] 
 435          ds.ref[':52@N'] = [52,   'V52N-HN',   1.57531,   0.15042,      6.51945,   1.43418,      13193.82986,   2307.09152,   93499.92172,    33233.23039,      0.3601317693,    0.1280037656] 
 436          ds.ref[':53@N'] = [53,   'A53N-HN',   1.27214,   0.13823,      4.0705,    0.85485,      13193.82986,   2307.09152,   34856.18636,    17505.02393,      0.1342548725,    0.0674237488] 
 437   
 438          ds.guess = dict() 
 439          ds.guess[':13@N'] = [13,   'L13N-HN',   1.32394,   0.14687,      8.16007,   1.01237,      13193.82986,   2307.09152,   58703.06446,    22413.09854,      0.2261054135,    0.0863280812] 
 440          ds.guess[':15@N'] = [15,   'R15N-HN',   1.34428,   0.14056,      7.83256,   0.67559,      13193.82986,   2307.09152,   28688.33492,    13480.72253,      0.110498283,     0.051923428] 
 441          ds.guess[':16@N'] = [16,   'T16N-HN',   1.71514,   0.13651,      17.44216,  0.98583,      13193.82986,   2307.09152,   57356.77617,    21892.44205,      0.220919942,     0.084322679] 
 442          ds.guess[':25@N'] = [25,   'Q25N-HN',   1.82412,   0.15809,      9.09447,   2.09215,      13193.82986,   2307.09152,   143111.13431,   49535.80302,      0.5512182797,    0.1907960569] 
 443          ds.guess[':26@N'] = [26,   'Q26N-HN',   1.45746,   0.14127,      10.22801,  0.67116,      13193.82986,   2307.09152,   28187.06876,    13359.01615,      0.1085675662,    0.051454654] 
 444          ds.guess[':28@N'] = [28,   'Q28N-HN',   1.48095,   0.14231,      10.33552,  0.691,        13193.82986,   2307.09152,   30088.0686,     13920.25654,      0.1158896091,    0.0536163723] 
 445          ds.guess[':39@N'] = [39,   'L39N-HN',   1.46094,   0.14514,      8.02194,   0.84649,      13193.82986,   2307.09152,   44130.18538,    18104.55064,      0.1699753481,    0.0697329338] 
 446          ds.guess[':40@N'] = [40,   'M40N-HN',   1.21381,   0.14035,      12.19112,  0.81418,      13193.82986,   2307.09152,   41834.90493,    17319.92156,      0.1611346625,    0.0667107938] 
 447          ds.guess[':41@N'] = [41,   'A41N-HN',   1.29296,   0.14286,      9.29941,   0.66246,      13193.82986,   2307.09152,   26694.8921,     13080.66782,      0.1028201794,    0.0503825453] 
 448          ds.guess[':43@N'] = [43,   'F43N-HN',   1.33626,   0.14352,      12.73816,  1.17386,      13193.82986,   2307.09152,   70347.63797,    26648.30524,      0.2709565833,    0.1026407417] 
 449          ds.guess[':44@N'] = [44,   'I44N-HN',   1.28487,   0.1462,       12.70158,  1.52079,      13193.82986,   2307.09152,   95616.20461,    35307.79817,      0.3682830136,    0.1359943366] 
 450          ds.guess[':45@N'] = [45,   'K45N-HN',   1.59227,   0.14591,      9.54457,   0.95596,      13193.82986,   2307.09152,   53849.7826,     21009.89973,      0.2074121253,    0.0809234085] 
 451          ds.guess[':49@N'] = [49,   'A49N-HN',   1.38521,   0.14148,      4.44842,   0.88647,      13193.82986,   2307.09152,   40686.65286,    18501.20774,      0.1567119631,    0.07126073] 
 452          ds.guess[':52@N'] = [52,   'V52N-HN',   1.57531,   0.15042,      6.51945,   1.43418,      13193.82986,   2307.09152,   93499.92172,    33233.23039,      0.3601317693,    0.1280037656] 
 453          ds.guess[':53@N'] = [53,   'A53N-HN',   1.27214,   0.13823,      4.0705,    0.85485,      13193.82986,   2307.09152,   34856.18636,    17505.02393,      0.1342548725,    0.0674237488] 
 454   
 455          # Assign guess values. 
 456          for spin, spin_id in spin_loop(return_id=True): 
 457              if spin_id in cluster_ids: 
 458                  print("spin_id %s in cluster ids"%(spin_id)) 
 459                  spin.kex = ds.guess[spin_id][6] 
 460                  spin.phi_ex = ds.guess[spin_id][10] 
 461              else: 
 462                  print("spin_id %s NOT in cluster ids"%(spin_id)) 
 463   
 464          if read_R1: 
 465              # Read the R1 data 
 466              self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
 467   
 468   
 469 -    def setup_hansen_cpmg_data(self, model=None): 
 470          """Set up the data for the test_hansen_cpmg_data_*() system tests. 
 471   
 472          @keyword model: The name of the model which will be tested. 
 473          @type model:    str 
 474          """ 
 475   
 476          # Create the data pipe and load the base data. 
 477          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
 478          self.interpreter.pipe.create(pipe_name='base pipe', pipe_type='relax_disp') 
 479          self.interpreter.results.read(data_path+sep+'base_pipe') 
 480          self.interpreter.deselect.spin(':4') 
 481   
 482          # Set the nuclear isotope data. 
 483          self.interpreter.spin.isotope('15N') 
 484   
 485          # Create the R2eff data pipe and load the results. 
 486          self.interpreter.pipe.create(pipe_name='R2eff - relax_disp', pipe_type='relax_disp') 
 487          self.interpreter.pipe.switch(pipe_name='R2eff - relax_disp') 
 488          self.interpreter.results.read(data_path+sep+'r2eff_pipe') 
 489          self.interpreter.deselect.spin(':4') 
 490   
 491          # The model data pipe. 
 492          pipe_name = "%s - relax_disp" % model 
 493          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 494          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 495   
 496          # Set the model. 
 497          self.interpreter.relax_disp.select_model(model=model) 
 498   
 499          # Copy the data. 
 500          self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to=pipe_name, param='r2eff') 
 501   
 502   
 503 -    def setup_kteilum_fmpoulsen_makke_cpmg_data(self, model=None, expfolder=None): 
 504          """Set up the data for the test_kteilum_fmpoulsen_makke_cpmg_data_*() system tests. 
 505   
 506          @keyword model: The name of the model which will be tested. 
 507          @type model:    str 
 508          """ 
 509   
 510          # Create the data pipe and load the base data. 
 511          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+expfolder 
 512          self.interpreter.pipe.create(pipe_name='base pipe', pipe_type='relax_disp') 
 513          self.interpreter.results.read(data_path+sep+'ini_setup_trunc') 
 514   
 515          # Create the R2eff data pipe and load the results. 
 516          self.interpreter.pipe.create(pipe_name='R2eff', pipe_type='relax_disp') 
 517          self.interpreter.pipe.switch(pipe_name='R2eff') 
 518          self.interpreter.results.read(data_path+sep+'r2eff_pipe_trunc') 
 519   
 520          # The model data pipe. 
 521          pipe_name = "%s - relax_disp" % model 
 522          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 523          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 524   
 525          # Set the model. 
 526          self.interpreter.relax_disp.select_model(model=model) 
 527   
 528          # Copy the data. 
 529          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
 530   
 531   
 532 -    def setup_korzhnev_2005_data(self, data_list=[]): 
 533          """Set up the data for the test_korzhnev_2005_data_*() system tests using the 'NS MMQ 2-site' model. 
 534   
 535          This loads the proton-heteronuclear SQ, ZQ, DQ, and MQ (MMQ) data from: 
 536   
 537              - Dmitry M. Korzhnev, Philipp Neudecker, Anthony Mittermaier, Vladislav Yu. Orekhov, and Lewis E. Kay (2005)  Multiple-site exchange in proteins studied with a suite of six NMR relaxation dispersion experiments: An application to the folding of a Fyn SH3 domain mutant.  127, 15602-15611 (U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}). 
 538   
 539          It consists of the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
 540   
 541   
 542          @keyword data_list: The list of data to load.  It can contain 'SQ', '1H SQ', 'ZQ', 'DQ', 'MQ', and '1H MQ'. 
 543          @type data_list:    list of str 
 544          """ 
 545   
 546          # Create the data pipe and load the base data. 
 547          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Korzhnev_et_al_2005' 
 548          self.interpreter.pipe.create(pipe_name='Korzhnev et al., 2005', pipe_type='relax_disp') 
 549   
 550          # Create the spin system. 
 551          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='H') 
 552          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='N') 
 553          self.interpreter.spin.element('H', spin_id='@H') 
 554          self.interpreter.spin.element('N', spin_id='@N') 
 555          self.interpreter.spin.isotope('1H', spin_id='@H') 
 556          self.interpreter.spin.isotope('15N', spin_id='@N') 
 557   
 558          # Define the magnetic dipole-dipole relaxation interaction. 
 559          self.interpreter.interatom.define(spin_id1=':9@N', spin_id2=':9@H', direct_bond=True) 
 560   
 561          # The spectral data - experiment ID, R2eff file name, experiment type, spin ID string, spectrometer frequency in Hertz, relaxation time. 
 562          data = [ 
 563              ['1H SQ', '1H_SQ_CPMG_500_MHz',  'hs_500.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 500e6, 0.03], 
 564              ['1H SQ', '1H_SQ_CPMG_600_MHz',  'hs_600.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 600e6, 0.03], 
 565              ['1H SQ', '1H_SQ_CPMG_800_MHz',  'hs_800.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 800e6, 0.03], 
 566              ['SQ',    '15N_SQ_CPMG_500_MHz', 'ns_500.res', EXP_TYPE_CPMG_SQ,        ':9@N', 500e6, 0.04], 
 567              ['SQ',    '15N_SQ_CPMG_600_MHz', 'ns_600.res', EXP_TYPE_CPMG_SQ,        ':9@N', 600e6, 0.04], 
 568              ['SQ',    '15N_SQ_CPMG_800_MHz', 'ns_800.res', EXP_TYPE_CPMG_SQ,        ':9@N', 800e6, 0.04], 
 569              ['DQ',    '15N_DQ_CPMG_500_MHz', 'dq_500.res', EXP_TYPE_CPMG_DQ,        ':9@N', 500e6, 0.03], 
 570              ['DQ',    '15N_DQ_CPMG_600_MHz', 'dq_600.res', EXP_TYPE_CPMG_DQ,        ':9@N', 600e6, 0.03], 
 571              ['DQ',    '15N_DQ_CPMG_800_MHz', 'dq_800.res', EXP_TYPE_CPMG_DQ,        ':9@N', 800e6, 0.03], 
 572              ['ZQ',    '15N_ZQ_CPMG_500_MHz', 'zq_500.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 500e6, 0.03], 
 573              ['ZQ',    '15N_ZQ_CPMG_600_MHz', 'zq_600.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 600e6, 0.03], 
 574              ['ZQ',    '15N_ZQ_CPMG_800_MHz', 'zq_800.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 800e6, 0.03], 
 575              ['1H MQ', '1H_MQ_CPMG_500_MHz',  'hm_500.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 500e6, 0.02], 
 576              ['1H MQ', '1H_MQ_CPMG_600_MHz',  'hm_600.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 600e6, 0.02], 
 577              ['1H MQ', '1H_MQ_CPMG_800_MHz',  'hm_800.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 800e6, 0.02], 
 578              ['MQ',    '15N_MQ_CPMG_500_MHz', 'nm_500.res', EXP_TYPE_CPMG_MQ,        ':9@N', 500e6, 0.02], 
 579              ['MQ',    '15N_MQ_CPMG_600_MHz', 'nm_600.res', EXP_TYPE_CPMG_MQ,        ':9@N', 600e6, 0.02], 
 580              ['MQ',    '15N_MQ_CPMG_800_MHz', 'nm_800.res', EXP_TYPE_CPMG_MQ,        ':9@N', 800e6, 0.02] 
 581          ] 
 582          cpmg_frqs_1h_sq = [67.0, 133.0, 267.0, 400.0, 533.0, 667.0, 800.0, 933.0, 1067.0, 1600.0, 2133.0, 2667.0] 
 583          cpmg_frqs_sq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
 584          cpmg_frqs_dq = [33.0, 67.0, 133.0, 200.0, 267.0, 333.0, 400.0, 467.0, 533.0, 667.0, 800.0, 933.0, 1067.0] 
 585          cpmg_frqs_zq = [33.0, 67.0, 133.0, 200.0, 267.0, 333.0, 400.0, 467.0, 533.0, 667.0, 800.0, 933.0, 1067.0] 
 586          cpmg_frqs_1h_mq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 400.0, 500.0, 600.0, 700.0, 800.0, 1000.0, 1500.0, 2000.0, 2500.0] 
 587          cpmg_frqs_mq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
 588   
 589          # Loop over the files, reading in the data. 
 590          for data_type, id, file, exp_type, spin_id, H_frq, relax_time in data: 
 591              # Skip undesired data. 
 592              if data_type not in data_list: 
 593                  continue 
 594   
 595              # Alias the CPMG frequencies. 
 596              if data_type == 'SQ': 
 597                  cpmg_frqs = cpmg_frqs_sq 
 598              elif data_type == '1H SQ': 
 599                  cpmg_frqs = cpmg_frqs_1h_sq 
 600              elif data_type == 'DQ': 
 601                  cpmg_frqs = cpmg_frqs_dq 
 602              elif data_type == 'ZQ': 
 603                  cpmg_frqs = cpmg_frqs_zq 
 604              elif data_type == '1H MQ': 
 605                  cpmg_frqs = cpmg_frqs_1h_mq 
 606              elif data_type == 'MQ': 
 607                  cpmg_frqs = cpmg_frqs_mq 
 608   
 609              # Loop over each CPMG frequency. 
 610              for cpmg_frq in cpmg_frqs: 
 611                  # The id. 
 612                  new_id = "%s_%s" % (id, cpmg_frq) 
 613   
 614                  # Set the NMR field strength. 
 615                  self.interpreter.spectrometer.frequency(id=new_id, frq=H_frq) 
 616   
 617                  # Set the relaxation dispersion experiment type. 
 618                  self.interpreter.relax_disp.exp_type(spectrum_id=new_id, exp_type=exp_type) 
 619   
 620                  # Relaxation dispersion CPMG constant time delay T (in s). 
 621                  self.interpreter.relax_disp.relax_time(spectrum_id=new_id, time=relax_time) 
 622   
 623                  # Set the CPMG frequency. 
 624                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=new_id, cpmg_frq=cpmg_frq) 
 625   
 626              # Read the R2eff data. 
 627              self.interpreter.relax_disp.r2eff_read_spin(id=id, file=file, dir=data_path, spin_id=spin_id, disp_point_col=1, data_col=2, error_col=3) 
 628   
 629          # Change the model. 
 630          self.interpreter.relax_disp.select_model('NS MMQ 2-site') 
 631   
 632   
 633 -    def setup_sod1wt_t25(self, pipe_name, pipe_type, pipe_name_r2eff, select_spin_index): 
 634          """Setup of data SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
 635   
 636          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
 637          'SOD1-WT' CPMG data to the CR72 dispersion model. 
 638   
 639          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
 640          Data is for experiment at 25 degree Celcius. 
 641          """ 
 642   
 643          # Create the data pipe and load the base data. 
 644          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'sod1wt_t25' 
 645   
 646          # Set experiment settings. sfrq, time_T2, ncyc 
 647          Exps = [ 
 648          ["600MHz", "Z_A", 599.8908617*1E6, 0.06, [28, 0, 4, 32, 60, 2, 10, 16, 8, 20, 50, 18, 40, 6, 12, 0, 24], ["Z_A1", "Z_A15"] ], 
 649          ["500MHz", "Z_B", 499.862139*1E6, 0.04, [20, 0, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28, 0], ["Z_B1", "Z_B18"] ] ] 
 650   
 651          # Create base pipe 
 652          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
 653   
 654          # Loop throug experiments 
 655          id_lists = [] 
 656          for folder, key, sfrq, time_T2, ncycs, rep_ncyss in Exps: 
 657              # Read spins 
 658              self.interpreter.spectrum.read_spins(file="128_FT.ser", dir=data_path+sep+folder) 
 659              self.interpreter.spectrum.read_spins(file="128_FT.ser", dir=data_path+sep+folder) 
 660   
 661              # Make spectrum id list 
 662              id_list = list(key+str(i) for i in range(len(ncycs))) 
 663              id_lists.append(id_list) 
 664   
 665              # Read intensities 
 666              self.interpreter.spectrum.read_intensities(file="128_FT.ser", dir=data_path+sep+folder, int_method='height', spectrum_id=id_list, int_col=list(range(len(id_list))) ) 
 667   
 668              # Loop over experiments 
 669              for i in range(len(ncycs)): 
 670                  ncyc = ncycs[i] 
 671                  vcpmg = ncyc/time_T2 
 672   
 673                  # Test if spectrum is a reference 
 674                  if float(vcpmg) == 0.0: 
 675                      vcpmg = None 
 676                  else: 
 677                      vcpmg = round(float(vcpmg), 3) 
 678   
 679                  # Set current id 
 680                  current_id = id_list[i] 
 681   
 682                  # Set the current experiment type. 
 683                  self.interpreter.relax_disp.exp_type(spectrum_id=current_id, exp_type='SQ CPMG') 
 684   
 685                  # Set the NMR field strength of the spectrum. 
 686                  self.interpreter.spectrometer.frequency(id=current_id, frq=sfrq, units='Hz') 
 687   
 688                  # Relaxation dispersion CPMG constant time delay T (in s). 
 689                  self.interpreter.relax_disp.relax_time(spectrum_id=current_id, time=time_T2) 
 690   
 691                  # Set the relaxation dispersion CPMG frequencies. 
 692                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=current_id, cpmg_frq=vcpmg) 
 693   
 694          # Define replicated 
 695          self.interpreter.spectrum.replicated(spectrum_ids=Exps[0][5]) 
 696          self.interpreter.spectrum.replicated(spectrum_ids=Exps[1][5]) 
 697   
 698          # Perform error analysis 
 699          self.interpreter.spectrum.error_analysis(subset=id_lists[0]) 
 700          self.interpreter.spectrum.error_analysis(subset=id_lists[1]) 
 701   
 702          # Define isotope 
 703          self.interpreter.spin.isotope(isotope='15N') 
 704   
 705          ############# 
 706   
 707          # Define the 64 residues which was used for Global fitting 
 708          glob_assn = ["G10N-H", "D11N-H", "Q15N-H", "G16N-H", "G37N-H", "G41N-H", "L42N-H", "H43N-H", "H46N-H", "V47N-H", "E49N-H", 
 709          "E50N-H", "E51N-H", "N53N-H", "T54N-H", "G56N-H", "C57N-H", "T58N-H", "G61N-H", "H63aN-H", "F64aN-H", "N65aN-H", 
 710          "L67N-H", "S68N-H", "K70N-H", "G72N-H", "G73N-H", "K75N-H", "E78N-H", "R79N-H", "H80N-H", "V81N-H", "G82N-H", 
 711          "G85N-H", "N86N-H", "V87N-H", "S102N-H", "V103N-H", "I104N-H", "S105N-H", "A111N-H", "I112N-H", "R115N-H", 
 712          "V118N-H", "E121N-H", "A123N-H", "L126N-H", "G127N-H", "K128N-H", "G129N-H", "G130N-H", "N131N-H", "E133N-H", 
 713          "S134N-H", "T135N-H", "T137N-H", "G138N-H", "N139N-H", "A140N-H", "G141N-H", "S142N-H", "R143N-H", "C146N-H", "G147N-H"] 
 714   
 715          # Test number of global 
 716          self.assertEqual(64, len(glob_assn )) 
 717   
 718          ## Turn assignments into relax spin ids. 
 719          # Define regular expression search 
 720          r = re.compile("([a-zA-Z]+)([0-9]+)([a-zA-Z]+)") 
 721   
 722          # Create list to hold regular expression search 
 723          relax_glob_ids = [] 
 724   
 725          # Loop over assignments 
 726          for assn in glob_assn: 
 727              # Make match for the regular search 
 728              m = r.match(assn) 
 729              # Convert to relax spin string 
 730              relax_string = ":%s@%s"%(m.group(2), m.group(3)) 
 731   
 732              # Save the relax spin string and the regular search 
 733              relax_glob_ids.append([m.group(0), m.group(1), m.group(2), m.group(3), relax_string]) 
 734   
 735          ############# Deselect all spins, and select few spins 
 736   
 737          ## Deselect all spins, and select a few for analysis 
 738          self.interpreter.deselect.all() 
 739   
 740          # Select few spins 
 741          for i in select_spin_index: 
 742              self.interpreter.select.spin(spin_id=relax_glob_ids[i][4], change_all=False) 
 743   
 744          ############## 
 745   
 746          # Prepare for R2eff calculation 
 747          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
 748          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
 749   
 750          # Select model for points calculation 
 751          MODEL = "R2eff" 
 752          self.interpreter.relax_disp.select_model(model=MODEL) 
 753          # Calculate R2eff values 
 754          self.interpreter.minimise.calculate(verbosity=1) 
 755   
 756   
 757 -    def setup_missing_r1_spins(self): 
 758          """Function for setting up a few spins for the given pipe.""" 
 759   
 760          # Path to file. 
 761          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
 762   
 763          # File with spins. 
 764          file = open(data_path+sep+'R1_fitted_values.txt') 
 765          lines = file.readlines() 
 766          file.close() 
 767   
 768          for i, line in enumerate(lines): 
 769              # Make the string test 
 770              line_split = line.split() 
 771   
 772              if line_split[0] == "#": 
 773                  continue 
 774   
 775              mol_name = line_split[0] 
 776              mol_name = None 
 777              res_num = int(line_split[1]) 
 778              res_name = line_split[2] 
 779              spin_num = line_split[3] 
 780              spin_num = None 
 781              spin_name = line_split[4] 
 782   
 783              # Create the spin. 
 784              self.interpreter.spin.create(spin_name=spin_name, spin_num=spin_num, res_name=res_name, res_num=res_num, mol_name=mol_name) 
 785   
 786   
 787 -    def setup_paul_schanda_nov_2015(self, outdir=None): 
 788          """This setup the truncated private data which was provided by Paul Schanda.""" 
 789   
 790          # Data path. 
 791          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Paul_Schanda_2015_Nov' 
 792          file = data_path + sep + '1_prepare_data.py' 
 793   
 794          # Store the out 
 795          status.outdir = outdir 
 796   
 797          # Run script. 
 798          self.interpreter.script(file=file, dir=None) 
 799   
 800   
 801 -    def setup_tp02_data_to_ns_r1rho_2site(self, clustering=False): 
 802          """Setup data for the test of relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data.""" 
 803   
 804          # Reset. 
 805          self.interpreter.reset() 
 806   
 807          # Create the data pipe and load the base data. 
 808          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02' 
 809          self.interpreter.state.load(data_path+sep+'r2eff_values') 
 810   
 811          # The model data pipe. 
 812          model = 'NS R1rho 2-site' 
 813          pipe_name = "%s - relax_disp" % model 
 814          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 815          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 816   
 817          # Set the model. 
 818          self.interpreter.relax_disp.select_model(model=model) 
 819   
 820          # Copy the data. 
 821          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
 822   
 823          # Alias the spins. 
 824          spin1 = cdp.mol[0].res[0].spin[0] 
 825          spin2 = cdp.mol[0].res[1].spin[0] 
 826   
 827          # The R20 keys. 
 828          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
 829          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
 830   
 831          # Set the initial parameter values. 
 832          spin1.r2 = {r20_key1: 9.9963793866185, r20_key2: 15.0056724422684} 
 833          spin1.pA = 0.779782428085762 
 834          spin1.dw = 7.57855284496424 
 835          spin1.kex = 1116.7911285203 
 836          spin2.r2 = {r20_key1: 11.9983346935434, r20_key2: 18.0076097513337} 
 837          spin2.pA = 0.826666229688602 
 838          spin2.dw = 9.5732624231366 
 839          spin2.kex = 1380.46162655657 
 840   
 841          # Test the values when clustering. 
 842          if clustering: 
 843              self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":1-100") 
 844   
 845          # Low precision optimisation. 
 846          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
 847   
 848          # Printout. 
 849          print("\n\nOptimised parameters:\n") 
 850          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
 851          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
 852          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
 853          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
 854          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
 855          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
 856          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
 857   
 858   
 859 -    def test_baldwin_synthetic(self): 
 860          """Test synthetic data of Andrew J. Baldwin B14 model  whereby the simplification R20A = R20B is assumed. 
 861   
 862          Support requst sr #3154 U{https://gna.org/support/index.php?3154}. 
 863   
 864          This uses the synthetic data from paper U{DOI: 10.1016/j.jmr.2014.02.023 <http://dx.doi.org/10.1016/j.jmr.2014.02.023>} with R20A, R20B = 2. rad/s. 
 865          """ 
 866   
 867          # The path to the data files. 
 868          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Baldwin_2014' 
 869   
 870          # Create pipe 
 871          pipe_name = 'base pipe' 
 872          pipe_type = 'relax_disp' 
 873          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
 874   
 875          # Create base pipe 
 876          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
 877   
 878          # Generate the sequence. 
 879          self.interpreter.spin.create(res_name='Ala', res_num=1, spin_name='H') 
 880   
 881          # Define the isotope. 
 882          self.interpreter.spin.isotope('1H', spin_id='@H') 
 883   
 884          # Build the experiment IDs. 
 885          # Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay) 
 886          ncycs = [2, 4, 8, 10, 20, 40, 500] 
 887          ids = [] 
 888          for ncyc in ncycs: 
 889              ids.append('CPMG_%s' % ncyc) 
 890   
 891          print("\n\nThe experiment IDs are %s." % ids) 
 892   
 893          # Set up the metadata for the experiments. 
 894          # This value is used in Baldwin.py. It is the 1H Larmor frequency. 
 895          sfrq = 200. * 1E6 
 896   
 897          # Total time of CPMG block. 
 898          Trelax = 0.04 
 899   
 900          # First set the 
 901          for i in range(len(ids)): 
 902              id = ids[i] 
 903              # Set the spectrometer frequency. 
 904              self.interpreter.spectrometer.frequency(id=id, frq=sfrq) 
 905   
 906              # Set the experiment type. 
 907              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
 908   
 909              # Set the relaxation dispersion CPMG constant time delay T (in s). 
 910              self.interpreter.relax_disp.relax_time(spectrum_id=id, time=Trelax) 
 911   
 912              # Set the relaxation dispersion CPMG frequencies. 
 913              ncyc = ncycs[i] 
 914              nu_cpmg = ncyc / Trelax 
 915              self.interpreter.relax_disp.cpmg_setup(spectrum_id=id, cpmg_frq=nu_cpmg) 
 916   
 917          # Prepare for R2eff reading. 
 918          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
 919          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
 920   
 921          # Try reading the R2eff file. 
 922          self.interpreter.relax_disp.r2eff_read_spin(id="CPMG", file="test_r2a_eq_r2b_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1, data_col=2, error_col=3) 
 923   
 924          # Check the global data. 
 925          data = [ 
 926              ['cpmg_frqs', {'CPMG_20': 500.0, 'CPMG_10': 250.0, 'CPMG_40': 1000.0, 'CPMG_4': 100.0, 'CPMG_2': 50.0, 'CPMG_500': 12500.0, 'CPMG_8': 200.0}], 
 927              ['cpmg_frqs_list', list(array(ncycs)/Trelax) ], 
 928              ['dispersion_points', len(ncycs)], 
 929              ['exp_type', {'CPMG_20': 'SQ CPMG', 'CPMG_10': 'SQ CPMG', 'CPMG_40': 'SQ CPMG', 'CPMG_4': 'SQ CPMG', 'CPMG_2': 'SQ CPMG', 'CPMG_500': 'SQ CPMG', 'CPMG_8': 'SQ CPMG'}], 
 930              ['exp_type_list', ['SQ CPMG']], 
 931              ['spectrometer_frq', {'CPMG_20': 200000000.0, 'CPMG_10': 200000000.0, 'CPMG_40': 200000000.0, 'CPMG_4': 200000000.0, 'CPMG_2': 200000000.0, 'CPMG_500': 200000000.0, 'CPMG_8': 200000000.0}], 
 932              ['spectrometer_frq_count', 1], 
 933              ['spectrometer_frq_list', [sfrq]], 
 934              ['spectrum_ids', ['CPMG_2', 'CPMG_4', 'CPMG_8', 'CPMG_10', 'CPMG_20', 'CPMG_40', 'CPMG_500']] 
 935          ] 
 936          for name, value in data: 
 937              # Does it exist? 
 938              self.assert_(hasattr(cdp, name)) 
 939   
 940              # Check the object. 
 941              obj = getattr(cdp, name) 
 942              if not isinstance(data, dict): 
 943                  self.assertEqual(obj, value) 
 944   
 945              # Check the global dictionary data. 
 946              else: 
 947                  for id in ids: 
 948                      self.assertEqual(obj[id], value[id]) 
 949   
 950          # Check the spin data. 
 951          n_data = [ 
 952              [ 50.000000, 10.367900, 0.1], 
 953              [ 100.000000, 10.146849, 0.1], 
 954              [ 200.000000, 9.765987, 0.1], 
 955              [ 250.000000, 9.409789, 0.1], 
 956              [ 500.000000, 5.829819, 0.1], 
 957              [ 1000.000000, 3.191928, 0.1], 
 958              [ 12500.000000, 2.008231, 0.1] 
 959          ] 
 960          for disp_point, value, error in n_data: 
 961              id = 'sq_cpmg_200.00000000_0.000_%.3f' % disp_point 
 962              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
 963              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
 964   
 965          # Generate r20 key. 
 966          r20_key = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq) 
 967   
 968          ## Now prepare for MODEL calculation. 
 969          MODEL = "B14" 
 970   
 971          # Change pipe. 
 972          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
 973          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
 974          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
 975   
 976          # Then select model. 
 977          self.interpreter.relax_disp.select_model(model=MODEL) 
 978   
 979          # Store grid and minimisations results. 
 980          grid_results = [] 
 981          mini_results = [] 
 982   
 983          # The grid search size (the number of increments per dimension). 
 984          # If None, use the default values. 
 985          #GRID = None 
 986          GRID = 13 
 987          # Perform Grid Search. 
 988          if GRID: 
 989              # Set the R20 parameters in the default grid search using the minimum R2eff value. 
 990              # This speeds it up considerably. 
 991              self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
 992   
 993              # Then do grid search. 
 994              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID, constraints=True, verbosity=1) 
 995   
 996              # If no Grid search, set the default values. 
 997          else: 
 998              for param in MODEL_PARAMS[MODEL]: 
 999                  self.interpreter.value.set(param=param, index=None) 
1000                  # Do a grid search, which will store the chi2 value. 
1001              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=1, constraints=True, verbosity=1) 
1002   
1003          # Store result. 
1004          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1005              grid_results.append([spin.r2[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1006   
1007          ## Now do minimisation. 
1008          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
1009          set_func_tol = 1e-10 
1010          set_max_iter = 1000 
1011          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1012   
1013          # Store result. 
1014          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1015              mini_results.append([spin.r2[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1016   
1017          # Print results. 
1018          for i in range(len(grid_results)): 
1019              g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
1020              m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
1021              print("GRID %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
1022              print("MIN  %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
1023   
1024          # Reference values from Baldwin.py. 
1025          # Exchange rate = k+ + k- (s-1) 
1026          kex = 1000. 
1027          # Fractional population of excited state k+/kex 
1028          pb = 0.01 
1029          # deltaOmega in ppm 
1030          dw_ppm = 2. 
1031          #relaxation rate of ground (s-1) 
1032          R2g = 2. 
1033          #relaxation rate of excited (s-1) 
1034          R2e = 2. 
1035   
1036          # Test the parameters which created the data. 
1037          # This is for the 1H spin. 
1038          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2[r20_key], R2g, 6) 
1039   
1040          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6) 
1041          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 8) 
1042          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex, kex, 3) 
1043   
1044   
1045 -    def test_baldwin_synthetic_full(self): 
1046          """Test synthetic data of Andrew J. Baldwin B14 model. Support requst sr #3154 U{https://gna.org/support/index.php?3154}. 
1047   
1048          This uses the synthetic data from paper U{DOI: 10.1016/j.jmr.2014.02.023 <http://dx.doi.org/10.1016/j.jmr.2014.02.023>}. 
1049          """ 
1050   
1051          # The path to the data files. 
1052          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Baldwin_2014' 
1053   
1054          # Create pipe 
1055          pipe_name = 'base pipe' 
1056          pipe_type = 'relax_disp' 
1057          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
1058   
1059          # Create base pipe 
1060          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
1061   
1062          # Generate the sequence. 
1063          # Generate both a 1H spin, and 15N spin. 
1064          self.interpreter.spin.create(res_name='Ala', res_num=1, spin_name='H') 
1065   
1066          # Define the isotope. 
1067          self.interpreter.spin.isotope('1H', spin_id='@H') 
1068   
1069          # Build the experiment IDs. 
1070          # Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay) 
1071          ncycs = [2, 4, 8, 10, 20, 40, 500] 
1072          ids = [] 
1073          for ncyc in ncycs: 
1074              ids.append('CPMG_%s' % ncyc) 
1075   
1076          print("\n\nThe experiment IDs are %s." % ids) 
1077   
1078          # Set up the metadata for the experiments. 
1079          # This value is used in Baldwin.py. It is the 1H Larmor frequency. 
1080          sfrq = 200. * 1E6 
1081   
1082          # Total time of CPMG block. 
1083          Trelax = 0.04 
1084   
1085          # First set the 
1086          for i in range(len(ids)): 
1087              id = ids[i] 
1088              # Set the spectrometer frequency. 
1089              self.interpreter.spectrometer.frequency(id=id, frq=sfrq) 
1090   
1091              # Set the experiment type. 
1092              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
1093   
1094              # Set the relaxation dispersion CPMG constant time delay T (in s). 
1095              self.interpreter.relax_disp.relax_time(spectrum_id=id, time=Trelax) 
1096   
1097              # Set the relaxation dispersion CPMG frequencies. 
1098              ncyc = ncycs[i] 
1099              nu_cpmg = ncyc / Trelax 
1100              self.interpreter.relax_disp.cpmg_setup(spectrum_id=id, cpmg_frq=nu_cpmg) 
1101   
1102          # Prepare for R2eff reading. 
1103          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
1104          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
1105   
1106          # Try reading the R2eff file. 
1107          self.interpreter.relax_disp.r2eff_read_spin(id="CPMG", file="test_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1, data_col=2, error_col=3) 
1108   
1109          # Check the global data. 
1110          data = [ 
1111              ['cpmg_frqs', {'CPMG_20': 500.0, 'CPMG_10': 250.0, 'CPMG_40': 1000.0, 'CPMG_4': 100.0, 'CPMG_2': 50.0, 'CPMG_500': 12500.0, 'CPMG_8': 200.0}], 
1112              ['cpmg_frqs_list', list(array(ncycs)/Trelax) ], 
1113              ['dispersion_points', len(ncycs)], 
1114              ['exp_type', {'CPMG_20': 'SQ CPMG', 'CPMG_10': 'SQ CPMG', 'CPMG_40': 'SQ CPMG', 'CPMG_4': 'SQ CPMG', 'CPMG_2': 'SQ CPMG', 'CPMG_500': 'SQ CPMG', 'CPMG_8': 'SQ CPMG'}], 
1115              ['exp_type_list', ['SQ CPMG']], 
1116              ['spectrometer_frq', {'CPMG_20': 200000000.0, 'CPMG_10': 200000000.0, 'CPMG_40': 200000000.0, 'CPMG_4': 200000000.0, 'CPMG_2': 200000000.0, 'CPMG_500': 200000000.0, 'CPMG_8': 200000000.0}], 
1117              ['spectrometer_frq_count', 1], 
1118              ['spectrometer_frq_list', [sfrq]], 
1119              ['spectrum_ids', ['CPMG_2', 'CPMG_4', 'CPMG_8', 'CPMG_10', 'CPMG_20', 'CPMG_40', 'CPMG_500']] 
1120          ] 
1121          for name, value in data: 
1122              # Does it exist? 
1123              self.assert_(hasattr(cdp, name)) 
1124   
1125              # Check the object. 
1126              obj = getattr(cdp, name) 
1127              if not isinstance(data, dict): 
1128                  self.assertEqual(obj, value) 
1129   
1130              # Check the global dictionary data. 
1131              else: 
1132                  for id in ids: 
1133                      self.assertEqual(obj[id], value[id]) 
1134   
1135          # Check the spin data. 
1136          n_data = [ 
1137              [ 50.000000, 10.286255, 0.1], 
1138              [ 100.000000, 10.073083, 0.1], 
1139              [ 200.000000, 9.692746, 0.1], 
1140              [ 250.000000, 9.382441, 0.1], 
1141              [ 500.000000, 6.312396, 0.1], 
1142              [ 1000.000000, 3.957029, 0.1], 
1143              [ 12500.000000, 2.880420, 0.1] 
1144          ] 
1145          for disp_point, value, error in n_data: 
1146              id = 'sq_cpmg_200.00000000_0.000_%.3f' % disp_point 
1147              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
1148              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
1149   
1150          # Generate r20 key. 
1151          r20_key = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq) 
1152   
1153          ## Now prepare for MODEL calculation. 
1154          MODEL = "B14 full" 
1155   
1156          # Change pipe. 
1157          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
1158          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
1159          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
1160   
1161          # Then select model. 
1162          self.interpreter.relax_disp.select_model(model=MODEL) 
1163   
1164          # Store grid and minimisations results. 
1165          grid_results = [] 
1166          mini_results = [] 
1167          clust_results = [] 
1168   
1169          # The grid search size (the number of increments per dimension). 
1170          # If None, use the default values. 
1171          #GRID = None 
1172          GRID = 13 
1173          # Perform Grid Search. 
1174          if GRID: 
1175              # Set the R20 parameters in the default grid search using the minimum R2eff value. 
1176              # This speeds it up considerably. 
1177              self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
1178   
1179              # Then do grid search. 
1180              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID, constraints=True, verbosity=1) 
1181   
1182              # If no Grid search, set the default values. 
1183          else: 
1184              for param in MODEL_PARAMS[MODEL]: 
1185                  self.interpreter.value.set(param=param, index=None) 
1186                  # Do a grid search, which will store the chi2 value. 
1187              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=1, constraints=True, verbosity=1) 
1188   
1189          # Store result. 
1190          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1191              grid_results.append([spin.r2a[r20_key], spin.r2b[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1192   
1193          ## Now do minimisation. 
1194          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
1195          set_func_tol = 1e-11 
1196          set_max_iter = 10000 
1197          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1198   
1199          # Store result. 
1200          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1201              mini_results.append([spin.r2a[r20_key], spin.r2b[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1202   
1203          print("\n# Now print before and after minimisation-\n") 
1204   
1205          # Print results. 
1206          for i in range(len(grid_results)): 
1207              g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
1208              m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
1209              print("GRID %s r2a=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
1210              print("MIN  %s r2b=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
1211   
1212          # Reference values from Baldwin.py. 
1213          # Exchange rate = k+ + k- (s-1) 
1214          kex = 1000. 
1215          # Fractional population of excited state k+/kex 
1216          pb = 0.01 
1217          # deltaOmega in ppm 
1218          dw_ppm = 2. 
1219          #relaxation rate of ground (s-1) 
1220          R2g = 2. 
1221          #relaxation rate of excited (s-1) 
1222          R2e = 100. 
1223   
1224          # Test the parameters which created the data. 
1225          # This is for the 1H spin. 
1226          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2a[r20_key], R2g, 3) 
1227          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2b[r20_key]/100, R2e/100, 3) 
1228   
1229          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6) 
1230          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 6) 
1231          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex/1000, kex/1000, 2) 
1232   
1233   
1234 -    def x_test_bmrb_sub_cpmg(self): 
1235          """U{Task #7858: <https://gna.org/task/?7858>} Make it possible to submit CPMG experiments for BMRB. 
1236          This uses CPMG data from: 
1237              - Webb H, Tynan-Connolly BM, Lee GM, Farrell D, O'Meara F, Soendergaard CR, Teilum K, Hewage C, McIntosh LP, Nielsen JE. 
1238                Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations. 
1239                (2011), Proteins: Struct, Funct, Bioinf 79(3):685-702, DOI 10.1002/prot.22886 
1240          """ 
1241   
1242          # Define path to data  
1243          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'HWebb_KTeilum_Proteins_Struct_Funct_Bioinf_2011' 
1244   
1245          # Read data. 
1246          self.interpreter.results.read(prev_data_path + sep + 'FT_-_CR72_-_min_-_128_-_free_spins') 
1247   
1248          # Set element 
1249          self.interpreter.spin.element(element='N', spin_id=':*@N', force=False) 
1250          #self.interpreter.spin.isotope(isotope='15N', spin_id=':*@N', force=False) 
1251          # Rename molecule from None to 'HEWL' 
1252          self.interpreter.molecule.name(mol_id=None, name='HEWL', force=True) 
1253          self.interpreter.molecule.type(mol_id='#HEWL', type='protein', force=False) 
1254   
1255          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1256              print(spin_id) 
1257              if resn == 'C': 
1258                  print(resi, resn) 
1259   
1260          # Select the thiol state of the system. 
1261          # 'all disulfide bound', 'all free', 'all other bound', 'disulfide and other bound', 'free and disulfide bound', 'free and other bound', 'free disulfide and other bound', 'not available', 'not present', 'not reported', 'unknown' 
1262          self.interpreter.bmrb.thiol_state(state='not reported') 
1263   
1264          # relax_data.temp_calibration(ri_id=None, method=None) 
1265   
1266          # Call display of bmrb. 
1267          self.interpreter.bmrb.display() 
1268   
1269   
1270 -    def test_bug_21081_disp_cluster_fail(self): 
1271          """U{Bug #21081<https://gna.org/bugs/?21081>} catch, the failure of a cluster analysis when spins are deselected.""" 
1272   
1273          # Clear the data store. 
1274          self.interpreter.reset() 
1275   
1276          # Load the state. 
1277          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states'+sep+'bug_21081_disp_cluster_fail.bz2' 
1278          self.interpreter.state.load(state, force=True) 
1279   
1280          # Model selection - to catch the failure. 
1281          self.interpreter.model_selection(method='AIC', modsel_pipe='final', bundle='relax_disp', pipes=['No Rex', 'CR72']) 
1282   
1283   
1284 -    def test_bug_21460_disp_cluster_fail(self): 
1285          """U{Bug #21460<https://gna.org/bugs/?21460>} catch, the failure due to a spectrometer frequency having no relaxation data.""" 
1286   
1287          # Clear the data store. 
1288          self.interpreter.reset() 
1289   
1290          # Load the state. 
1291          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states'+sep+'bug_21460_bad_fields.bz2' 
1292          self.interpreter.state.load(state, force=True) 
1293   
1294          # Execute the auto-analysis (fast). 
1295          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1296          relax_disp.Relax_disp.opt_max_iterations = 1000 
1297          relax_disp.Relax_disp(pipe_name="origin - relax_disp (Thu Jan  2 13:46:44 2014)", pipe_bundle="relax_disp (Thu Jan  2 13:46:44 2014)", results_dir=self.tmpdir, models=['R2eff', 'No Rex', 'CR72', 'NS CPMG 2-site expanded'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1298   
1299   
1300 -    def test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp(self): 
1301          """U{Bug #21665<https://gna.org/bugs/?21344>} catch, the failure of an analysis of a sparse acquired R1rho dataset with missing combinations of time and spin-lock field strengths using auto_analysis.""" 
1302   
1303          # Clear the data store. 
1304          self.interpreter.reset() 
1305   
1306          # Load the state. 
1307          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
1308          self.interpreter.state.load(state, force=True) 
1309   
1310          # Execute the auto-analysis (fast). 
1311          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1312          relax_disp.Relax_disp.opt_max_iterations = 1000 
1313          relax_disp.Relax_disp(pipe_name='base pipe', pipe_bundle='relax_disp', results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1314   
1315   
1316 -    def test_bug_21665_cpmg_two_fields_two_delaytimes_fail_calc(self): 
1317          """U{Bug #21665<https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times, using minimise.calculate().""" 
1318   
1319          # Clear the data store. 
1320          self.interpreter.reset() 
1321   
1322          # Load the state. 
1323          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2' 
1324          self.interpreter.state.load(state, force=True) 
1325   
1326          # Run the calculation. 
1327          self.interpreter.minimise.calculate(verbosity=1) 
1328   
1329   
1330 -    def test_bug_21665_cpmg_two_fields_two_delaytimes_fail_relax_disp(self): 
1331          """U{Bug #21665<https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times using auto_analysis.""" 
1332   
1333          # Clear the data store. 
1334          self.interpreter.reset() 
1335   
1336          # Load the state. 
1337          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2' 
1338          self.interpreter.state.load(state, force=True) 
1339   
1340          # Execute the auto-analysis (fast). 
1341          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1342          relax_disp.Relax_disp.opt_max_iterations = 1000 
1343          relax_disp.Relax_disp(pipe_name="compare_128_FT_R2eff", pipe_bundle="cpmg_disp_sod1d90a", results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1344   
1345   
1346 -    def test_bug_21715_clustered_indexerror(self): 
1347          """Catch U{bug #21715<https://gna.org/bugs/?21715>}, the failure of a clustered auto-analysis due to an IndexError.""" 
1348   
1349          # Clear the data store. 
1350          self.interpreter.reset() 
1351   
1352          # Load the state. 
1353          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21715_clustered_indexerror'+sep+'state.bz2' 
1354          self.interpreter.state.load(state, force=True) 
1355   
1356          # Execute the auto-analysis (fast). 
1357          pre_run_dir = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21715_clustered_indexerror'+sep+'non_clustered' 
1358          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1359          relax_disp.Relax_disp.opt_max_iterations = 1000 
1360          relax_disp.Relax_disp(pipe_name='origin - relax_disp (Sun Feb 23 19:36:51 2014)', pipe_bundle='relax_disp (Sun Feb 23 19:36:51 2014)', results_dir=self.tmpdir, models=['R2eff', 'No Rex'], grid_inc=11, mc_sim_num=3, modsel='AIC', pre_run_dir=pre_run_dir, insignificance=1.0, numeric_only=True, mc_sim_all_models=False, eliminate=True) 
1361   
1362   
1363 -    def test_bug_22146_unpacking_r2a_r2b_cluster_B14(self): 
1364          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered B14 full analysis.""" 
1365   
1366          # Base data setup. 
1367          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='B14_full', model_analyse = MODEL_B14_FULL) 
1368   
1369   
1370 -    def test_bug_22146_unpacking_r2a_r2b_cluster_CR72(self): 
1371          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered CR72 full analysis.""" 
1372   
1373          # Base data setup. 
1374          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='CR72_full', model_analyse = MODEL_CR72_FULL) 
1375   
1376   
1377 -    def test_bug_22146_unpacking_r2a_r2b_cluster_NS_3D(self): 
1378          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered NS CPMG 2SITE 3D full analysis.""" 
1379   
1380          # Base data setup. 
1381          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='ns_cpmg_2site_3d_full', model_analyse = MODEL_NS_CPMG_2SITE_3D_FULL) 
1382   
1383   
1384 -    def test_bug_22146_unpacking_r2a_r2b_cluster_NS_STAR(self): 
1385          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered NS CPMG 2SITE STAR full analysis.""" 
1386   
1387          # Base data setup. 
1388          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='ns_cpmg_2site_star_full', model_analyse = MODEL_NS_CPMG_2SITE_STAR_FULL, places = 4) 
1389   
1390   
1391 -    def test_bug_22477_grace_write_k_AB_mixed_analysis(self): 
1392          """Catch U{bug #22146<https://gna.org/bugs/?22477>}, the failure of issuing: grace.write(x_data_type='res_num', y_data_type=param) for a mixed CPMG analysis.""" 
1393   
1394          # Clear the data store. 
1395          self.interpreter.reset() 
1396   
1397          # Load the state. 
1398          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_22477_grace_write_k_AB_mixed_analysis'+sep+'bug_22477_results.bz2' 
1399          self.interpreter.state.load(state, force=True) 
1400   
1401          param = 'k_AB' 
1402   
1403          for spin, spin_id in spin_loop(return_id=True, skip_desel=True): 
1404              print(spin_id, spin.params) 
1405              if param in spin.params: 
1406                  print(spin_id, spin.k_AB, spin.k_AB_err) 
1407   
1408          # Perform write. 
1409          self.interpreter.grace.write(x_data_type='res_num', y_data_type=param, file='%s.agr'%param, dir=self.tmpdir, force=True) 
1410   
1411   
1412          # Test the header of the value.write  parameter r2. 
1413          param = 'r2' 
1414          self.interpreter.value.write(param=param, file='%s.out'%param, dir=self.tmpdir, force=True) 
1415   
1416          file = open(self.tmpdir+sep+'%s.out'%param) 
1417          lines = file.readlines() 
1418          file.close() 
1419   
1420          for i, line in enumerate(lines): 
1421              # Make the string test 
1422              line_split = line.split() 
1423              print(line_split) 
1424   
1425              if len(line_split) > 1: 
1426                  # Break at parameter header. 
1427                  if line_split[0] == "#" and line_split[1] == 'mol_name': 
1428                      nr_split_header = len(line_split) 
1429                      nr_split_header_i = i 
1430                      break 
1431   
1432          # Call the line after. 
1433          line_split_val = lines[nr_split_header_i + 1].split() 
1434          print(line_split_val) 
1435   
1436          # Assert that the number of columns is equal, plus 1 for "#". 
1437          self.assertEqual(nr_split_header, len(line_split_val) + 1) 
1438   
1439          # Test the header of the value.write for parameter r2eff. 
1440          param = 'r2eff' 
1441          self.interpreter.value.write(param=param, file='%s.out'%param, dir=self.tmpdir, force=True) 
1442   
1443          file = open(self.tmpdir+sep+'%s.out'%param) 
1444          lines = file.readlines() 
1445          file.close() 
1446   
1447          for i, line in enumerate(lines): 
1448              # Make the string test 
1449              line_split = line.split() 
1450              print(line_split) 
1451   
1452              if len(line_split) > 1: 
1453                  # Break at parameter header. 
1454                  if line_split[0] == "#" and line_split[1] == 'mol_name': 
1455                      nr_split_header = len(line_split) 
1456                      nr_split_header_i = i 
1457                      break 
1458   
1459          # Call the line after. 
1460          line_split_val = lines[nr_split_header_i + 1].split() 
1461          print(line_split_val) 
1462   
1463          # Assert that the number of columns is equal, plus 1 for "#". 
1464          self.assertEqual(nr_split_header, len(line_split_val) + 1) 
1465   
1466   
1467 -    def test_bug_23186_cluster_error_calc_dw(self): 
1468          """Catch U{bug #23186<https://gna.org/bugs/?23186>}: Error calculation of individual parameter "dw" from Monte-Carlo, is based on first spin.""" 
1469   
1470          # Clear the data store. 
1471          self.interpreter.reset() 
1472   
1473          # Load the state. 
1474          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_23186.bz2' 
1475          self.interpreter.state.load(state, force=True) 
1476   
1477          # Dic key to spectrometer frq. 
1478          dickey = 'SQ CPMG - 599.89086220 MHz' 
1479   
1480          # First get the resi 0 array of sim r2a. 
1481          resi_0_r2a = [] 
1482   
1483          # Assign spins 
1484          res0 = cdp.mol[0].res[0].spin[0] 
1485          res1 = cdp.mol[0].res[1].spin[0] 
1486   
1487          print("Chi2 before call to minimise: %3.3f"%res0.chi2) 
1488          self.interpreter.minimise.execute(min_algor='simplex', max_iter=100000, verbosity=0) 
1489          print("Chi2 after call to minimise: %3.3f"%res0.chi2) 
1490   
1491          # Loop over the dics in spin. 
1492          for cdic in res0.r2a_sim: 
1493              resi_0_r2a.append(cdic[dickey]) 
1494   
1495          # Get stats with numpy 
1496          resi_0_r2a_std = std(asarray(resi_0_r2a), ddof=1) 
1497   
1498          # First get the resi 86 array of sim r2a. 
1499          resi_86_r2a = [] 
1500   
1501          # Loop over the dics in spin. 
1502          for cdic in res1.r2a_sim: 
1503              resi_86_r2a.append(cdic[dickey]) 
1504   
1505          # Get stats with numpy 
1506          resi_86_r2a_std = std(asarray(resi_86_r2a), ddof=1) 
1507   
1508          # Then get for dw. 
1509   
1510          # First get the array of sim dw. 
1511          resi_0_dw = res0.dw_sim 
1512          resi_86_dw = res1.dw_sim 
1513   
1514          # Get stats with numpy 
1515          resi_0_dw_std = std(asarray(resi_0_dw), ddof=1) 
1516          resi_86_dw_std = std(asarray(resi_86_dw), ddof=1) 
1517   
1518          # Then get for spin independent parameter. 
1519   
1520          # First get the array of sim dw. 
1521          resi_0_kAB = res0.k_AB_sim 
1522          resi_86_kAB = res1.k_AB_sim 
1523   
1524          # Get stats with numpy 
1525          resi_0_kAB_std = std(asarray(resi_0_kAB), ddof=1) 
1526          resi_86_kAB_std = std(asarray(resi_0_kAB), ddof=1) 
1527   
1528          # Assume they both std of k_AB values are equal 
1529          self.assertEqual(resi_0_kAB_std, resi_86_kAB_std) 
1530   
1531          # Perform error analysis. 
1532          self.interpreter.monte_carlo.error_analysis() 
1533   
1534          # Check values for k_AB. 
1535          self.assertAlmostEqual(resi_0_kAB_std, res0.k_AB_err) 
1536          self.assertAlmostEqual(resi_86_kAB_std, res1.k_AB_err) 
1537   
1538          # Check values for r2a. 
1539          self.assertAlmostEqual(resi_0_r2a_std, res0.r2a_err[dickey]) 
1540          self.assertAlmostEqual(resi_86_r2a_std, res1.r2a_err[dickey]) 
1541   
1542          # Check values for dw. 
1543          self.assertAlmostEqual(resi_0_dw_std, res0.dw_err) 
1544          self.assertAlmostEqual(resi_86_dw_std, res1.dw_err) 
1545   
1546          # The following is for Bug #23619: (https://gna.org/bugs/index.php?23619): Stored chi2 sim values from Monte-Carlo simulations does not equal normal chi2 values. 
1547          # This is to show that this bug is invalid. The "very" different chi2 values stems from r2eff points being back-calculated values rather than original measured values. 
1548   
1549          # Check calculates the same Monte-Carlo chi2 values  
1550          self.interpreter.monte_carlo.setup(number=3) 
1551          self.interpreter.monte_carlo.create_data(method='back_calc') 
1552          self.interpreter.monte_carlo.initial_values() 
1553   
1554          # Assign original data instead of back_calculated error. 
1555          res0.r2eff_sim[0] = copy.copy(res0.r2eff) 
1556          res0.r2eff_sim[1] = copy.copy(res0.r2eff) 
1557          res0.r2eff_sim[2] = copy.copy(res0.r2eff) 
1558          res1.r2eff_sim[0] = copy.copy(res1.r2eff) 
1559          res1.r2eff_sim[1] = copy.copy(res1.r2eff) 
1560          res1.r2eff_sim[2] = copy.copy(res1.r2eff) 
1561   
1562          self.interpreter.minimise.execute(min_algor='simplex', max_iter=100000) 
1563          self.interpreter.monte_carlo.error_analysis() 
1564   
1565          # Get the simulation array and calculate the average 
1566          spin_chi2_mc = res0.chi2 
1567          spin_chi2_mc_sim = res0.chi2_sim 
1568          spin_chi2_mc_sim_ave = average(spin_chi2_mc_sim) 
1569   
1570          print("The chi2 from calculation is: %3.3f"%spin_chi2_mc) 
1571          print("The array with monte-carlo chi2 values is: %s"%spin_chi2_mc_sim) 
1572          print("The average of this array is: %3.3f"%spin_chi2_mc_sim_ave) 
1573   
1574          self.assertAlmostEqual(spin_chi2_mc, spin_chi2_mc_sim_ave, 7) 
1575   
1576   
1577 -    def test_bug_9999_slow_r1rho_r2eff_error_with_mc(self): 
1578          """Catch U{bug #9999<https://gna.org/bugs/?9999>}, The slow optimisation of R1rho R2eff error estimation with Monte Carlo simulations.""" 
1579   
1580          # Define path to data  
1581          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000"  +sep+ "R2eff" 
1582   
1583          # Read data. 
1584          self.interpreter.results.read(prev_data_path + sep + 'results')         
1585   
1586          # Now count number 
1587          graph_nr = 1 
1588          for exp_type, frq, offset, point in loop_exp_frq_offset_point(return_indices=False): 
1589              print("\nGraph nr %i" % graph_nr) 
1590              for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
1591                  print(exp_type, frq, offset, point, time) 
1592              graph_nr += 1 
1593   
1594          ## Possibly do an error analysis. 
1595   
1596          # Check if intensity errors have already been calculated by the user. 
1597          precalc = True 
1598          for spin in spin_loop(skip_desel=True): 
1599              # No structure. 
1600              if not hasattr(spin, 'peak_intensity_err'): 
1601                  precalc = False 
1602                  break 
1603   
1604              # Determine if a spectrum ID is missing from the list. 
1605              for id in cdp.spectrum_ids: 
1606                  if id not in spin.peak_intensity_err: 
1607                      precalc = False 
1608                      break 
1609   
1610          # Skip. 
1611          if precalc: 
1612              print("Skipping the error analysis as it has already been performed.") 
1613   
1614          else: 
1615              # Loop over the spectrometer frequencies. 
1616              for frq in loop_frq(): 
1617                  # Generate a list of spectrum IDs matching the frequency. 
1618                  ids = [] 
1619                  for id in cdp.spectrum_ids: 
1620                      # Check that the spectrometer frequency matches. 
1621                      match_frq = True 
1622                      if frq != None and cdp.spectrometer_frq[id] != frq: 
1623                          match_frq = False 
1624   
1625                      # Add the ID. 
1626                      if match_frq: 
1627                          ids.append(id) 
1628   
1629                  # Run the error analysis on the subset. 
1630                  self.interpreter.spectrum.error_analysis(subset=ids) 
1631   
1632          print("has_exponential_exp_type:", has_exponential_exp_type()) 
1633   
1634          model = 'R2eff' 
1635          self.interpreter.relax_disp.select_model(model) 
1636   
1637          for spin, spin_id in spin_loop(return_id=True, skip_desel=True): 
1638              #delattr(spin, 'r2eff') 
1639              #delattr(spin, 'r2eff_err') 
1640              #delattr(spin, 'i0') 
1641              #delattr(spin, 'i0_err') 
1642              setattr(spin, 'r2eff', {}) 
1643              setattr(spin, 'r2eff_err', {}) 
1644              setattr(spin, 'i0', {}) 
1645              setattr(spin, 'i0_err', {}) 
1646   
1647          # Do Grid Search 
1648          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=21, constraints=True, verbosity=1) 
1649   
1650          # Start dic. 
1651          my_dic = {} 
1652   
1653          # Define counter for maximum elements in the numpy array list 
1654          NE = 0 
1655          NS = 1 
1656          NM = 0 
1657          NO = 0 
1658          ND = 0 
1659          NT = 0 
1660   
1661          for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1662              # Save to counter. 
1663              if ei > NE: 
1664                  NE = ei 
1665              if mi > NM: 
1666                  NM = mi 
1667              if oi > NO: 
1668                  NO = oi 
1669              if di > ND: 
1670                 ND = di 
1671   
1672              for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1673                  # Save to counter. 
1674                  if ti > NT: 
1675                      NT = ti 
1676   
1677          # Add 1 to counter, since index start from 0. 
1678          NE = NE + 1 
1679          NM = NM + 1  
1680          NO = NO + 1 
1681          ND = ND + 1 
1682          NT = NT + 1 
1683   
1684          # Make data array. 
1685          values_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1686          errors_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1687          times_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1688          struct_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1689          param_key_list = [] 
1690   
1691   
1692          # Loop over each spectrometer frequency and dispersion point. 
1693          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1694              # Add key to dic. 
1695              my_dic[spin_id] = {} 
1696   
1697              # Generate spin string. 
1698              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1699   
1700              # Loop over the parameters. 
1701              #print("Grid optimised parameters for spin: %s" % (spin_string)) 
1702   
1703              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1704                  # Generate the param_key. 
1705                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1706   
1707                  # Append key. 
1708                  param_key_list.append(param_key) 
1709   
1710                  # Add key to dic. 
1711                  my_dic[spin_id][param_key] = {} 
1712   
1713                  # Get the value. 
1714                  R2eff_value = getattr(cur_spin, 'r2eff')[param_key] 
1715                  i0_value = getattr(cur_spin, 'i0')[param_key] 
1716   
1717                  # Save to dic. 
1718                  my_dic[spin_id][param_key]['R2eff_value_grid'] = R2eff_value 
1719                  my_dic[spin_id][param_key]['i0_value_grid'] = i0_value 
1720   
1721                  ## Now try do a line of best fit by least squares. 
1722                  # The peak intensities, errors and times. 
1723                  values = [] 
1724                  errors = [] 
1725                  times = [] 
1726                  for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1727                      value = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, sim_index=None) 
1728                      values.append(value) 
1729   
1730                      error = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True) 
1731                      errors.append(error) 
1732                      times.append(time) 
1733   
1734                      # Save to numpy arrays. 
1735                      values_arr[ei, 0, mi, oi, di, ti] = value 
1736                      errors_arr[ei, 0, mi, oi, di, ti] = error 
1737                      times_arr[ei, 0, mi, oi, di, ti] = time 
1738                      struct_arr[ei, 0, mi, oi, di, ti] = 1.0 
1739   
1740                  # y= A exp(x * k) 
1741                  # w[i] = ln(y[i]) 
1742                  # int[i] = i0 * exp( - times[i] * r2eff); 
1743                  w = log(array(values)) 
1744                  x = - array(times) 
1745                  n = len(times) 
1746   
1747                  b = (sum(x*w) - 1./n * sum(x) * sum(w) ) / ( sum(x**2) - 1./n * (sum(x))**2 ) 
1748                  a = 1./n * sum(w) - b * 1./n * sum(x) 
1749                  R2eff_est = b 
1750                  i0_est = exp(a) 
1751   
1752                  my_dic[spin_id][param_key]['R2eff_est'] = R2eff_est 
1753                  my_dic[spin_id][param_key]['i0_est'] = i0_est 
1754   
1755                  # Print value. 
1756                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'R2eff', "Value : Estimated:", R2eff_value, R2eff_est)) 
1757                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'i0', "Value: Estimated:", i0_value, i0_est)) 
1758   
1759   
1760          # Do minimisation. 
1761          set_func_tol = 1e-25 
1762          set_max_iter = int(1e7) 
1763          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1764   
1765          # Loop over each spectrometer frequency and dispersion point. 
1766          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1767              # Generate spin string. 
1768              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1769   
1770              # Loop over the parameters. 
1771              print("Optimised parameters for spin: %s" % (spin_string)) 
1772   
1773              for exp_type, frq, offset, point in loop_exp_frq_offset_point(): 
1774                  # Generate the param_key. 
1775                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1776   
1777                  # Get the value. 
1778                  R2eff_value = getattr(cur_spin, 'r2eff')[param_key] 
1779                  i0_value = getattr(cur_spin, 'i0')[param_key] 
1780   
1781                  # Extract from dic. 
1782                  R2eff_value_grid = my_dic[spin_id][param_key]['R2eff_value_grid'] 
1783                  i0_value_grid = my_dic[spin_id][param_key]['i0_value_grid'] 
1784                  R2eff_est = my_dic[spin_id][param_key]['R2eff_est'] 
1785                  i0_est = my_dic[spin_id][param_key]['i0_est'] 
1786   
1787                  # Print value. 
1788                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'R2eff', "Value : Estimated:", R2eff_value, R2eff_est)) 
1789                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'i0', "Value: Estimated:", i0_value, i0_est)) 
1790   
1791                  print("%-10s %-6s %-6s %3.1f : %3.1f: %3.1f" % ("Parameter:", 'R2eff', "Grid : Min : Estimated:", R2eff_value_grid, R2eff_value, R2eff_est)) 
1792                  print("%-10s %-6s %-6s %3.1f : %3.1f: %3.1f" % ("Parameter:", 'i0', "Grid : Min : Estimated:", i0_value_grid, i0_value, i0_est)) 
1793   
1794          print(NE, NS, NM, NO, ND, NT) 
1795          for param_key in param_key_list: 
1796              print("        '%s'," % param_key) 
1797          print(values_arr.shape) 
1798   
1799          # Save arrays to profiling. 
1800          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'curve_fitting'+sep+'profiling'+sep 
1801          #save(data_path + "values_arr", values_arr) 
1802          #save(data_path + "errors_arr", errors_arr) 
1803          #save(data_path + "times_arr", times_arr) 
1804          #save(data_path + "struct_arr", struct_arr) 
1805   
1806   
1807 -    def test_bug_atul_srivastava(self): 
1808          """Test data from Atul Srivastava.  This is a bug missing raising a Relax Error, since the setup points to a situation where the data 
1809          shows it is exponential fitting, but only one time point is added per file. 
1810   
1811          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1718>}: 
1812          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1735>}: 
1813          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1735/focus=1736>}: 
1814   
1815          """ 
1816   
1817          # Data path. 
1818          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_Atul_Srivastava' 
1819          file = data_path + sep + 'bug_script.py' 
1820   
1821          # Run script. 
1822          self.interpreter.script(file=file, dir=None) 
1823   
1824          # The grid search size (the number of increments per dimension). 
1825          GRID_INC = 11 
1826   
1827          # Check-data. 
1828          ################# 
1829   
1830          # Loop over spins, to see current setup. 
1831          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1832              print(mol_name, resi, resn, spin_id) 
1833   
1834          # Loop over setup. 
1835          for id in cdp.exp_type: 
1836              print(id, cdp.exp_type[id], cdp.spectrometer_frq[id], cdp.spin_lock_offset[id], cdp.spin_lock_nu1[id]) 
1837   
1838   
1839          # Manual minimisation. 
1840          ################# 
1841          if True: 
1842              # Set the model. 
1843              self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
1844   
1845              # Check if intensity errors have already been calculated. 
1846              check_intensity_errors() 
1847   
1848              # Calculate the R2eff values for the fixed relaxation time period data types. 
1849              if cdp.model_type == MODEL_R2EFF and not has_exponential_exp_type(): 
1850                  self.interpreter.minimise.calculate() 
1851   
1852              # Optimise the model. 
1853              else: 
1854                  constraints = False 
1855                  min_algor = 'Newton' 
1856                  self.assertRaises(RelaxError, self.interpreter.minimise.grid_search, inc=GRID_INC) 
1857                  self.assertRaises(RelaxError, self.interpreter.minimise.execute, min_algor=min_algor, constraints=constraints) 
1858   
1859          # Inspect. 
1860          if False: 
1861              # Loop over attributes. 
1862              par_attr_list = ['r2eff', 'i0'] 
1863   
1864              # Collect the estimation data. 
1865              my_dic = {} 
1866              param_key_list = [] 
1867              est_keys = [] 
1868              est_key = 'grid' 
1869              est_keys.append(est_key) 
1870              spin_id_list = [] 
1871   
1872              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1873                  # Add key to dic. 
1874                  my_dic[spin_id] = {} 
1875   
1876                  # Add key for estimate. 
1877                  my_dic[spin_id][est_key] = {} 
1878   
1879                  # Add spin key to list. 
1880                  spin_id_list.append(spin_id) 
1881   
1882                  # Generate spin string. 
1883                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1884   
1885                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1886                      # Generate the param_key. 
1887                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1888                      #param_key = generate_r20_key(exp_type=exp_type, frq=frq) 
1889   
1890                      # Append key. 
1891                      param_key_list.append(param_key) 
1892   
1893                      # Add key to dic. 
1894                      my_dic[spin_id][est_key][param_key] = {} 
1895   
1896                      # Get the value. 
1897                      # Loop over err attributes. 
1898                      for par_attr in par_attr_list: 
1899                          if hasattr(cur_spin, par_attr): 
1900                              get_par_attr = getattr(cur_spin, par_attr)[param_key] 
1901                          else: 
1902                              get_par_attr = 0.0 
1903   
1904                          # Save to dic. 
1905                          my_dic[spin_id][est_key][param_key][par_attr] = get_par_attr 
1906   
1907                      # Check number of values. 
1908                      values = [] 
1909                      errors = [] 
1910                      times = [] 
1911                      for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1912                          value = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, sim_index=None) 
1913                          values.append(value) 
1914   
1915                          error = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True) 
1916                          errors.append(error) 
1917                          times.append(time) 
1918   
1919                      # Save to dic. 
1920                      my_dic[spin_id][est_key][param_key]['values'] = values 
1921                      my_dic[spin_id][est_key][param_key]['errors'] = errors 
1922                      my_dic[spin_id][est_key][param_key]['times'] = times 
1923   
1924          # Analysis variables. 
1925          ##################### 
1926   
1927          # The dispersion models. 
1928          MODELS = ['R2eff', 'No Rex'] 
1929   
1930          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
1931          MC_NUM = 10 
1932   
1933          # A flag which if True will activate Monte Carlo simulations for all models.  Note this will hugely increase the computation time. 
1934          MC_SIM_ALL_MODELS = False 
1935   
1936          # The results directory. 
1937          RESULTS_DIR = ds.tmpdir 
1938   
1939          # The directory of results of an earlier analysis without clustering. 
1940          PRE_RUN_DIR = None 
1941   
1942          # The model selection technique to use. 
1943          MODSEL = 'AIC' 
1944   
1945          # The flag for only using numeric models in the final model selection. 
1946          NUMERIC_ONLY = False 
1947   
1948          # The R1rho value in rad/s by which to judge insignificance.  If the maximum difference between two points on all dispersion curves for a spin is less than this value, that spin will be deselected. 
1949          INSIGNIFICANCE = 1.0 
1950   
1951          # Auto-analysis execution. 
1952          self.assertRaises(RelaxError, relax_disp.Relax_disp, pipe_name='relax_disp', results_dir=RESULTS_DIR, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, insignificance=INSIGNIFICANCE, numeric_only=NUMERIC_ONLY) 
1953   
1954   
1955 -    def test_bug_negative_intensities_cpmg(self): 
1956          """Test data, where peak intensities are negative in CPMG 
1957   
1958          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
1959          """ 
1960   
1961          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+'bug_neg_int_acbp_cpmg_disp_048MGuHCl_40C_041223' 
1962   
1963          # Create the spins 
1964          self.interpreter.spectrum.read_spins(file="peaks_list_max_standard.ser", dir=data_path) 
1965   
1966          # Name the isotope for field strength scaling. 
1967          self.interpreter.spin.isotope(isotope='15N') 
1968   
1969          # Read the spectrum from NMRSeriesTab file. The "auto" will generate spectrum name of form: Z_A{i} 
1970          self.interpreter.spectrum.read_intensities(file="peaks_list_max_standard.ser", dir=data_path, spectrum_id='auto', int_method='height') 
1971   
1972          # Loop over the spectra settings. 
1973          ncycfile=open(data_path + sep + 'ncyc.txt', 'r') 
1974   
1975          # Make empty ncyclist 
1976          ncyclist = [] 
1977   
1978          i = 0 
1979          for line in ncycfile: 
1980              ncyc = line.split()[0] 
1981              time_T2 = float(line.split()[1]) 
1982              vcpmg = line.split()[2] 
1983              set_sfrq = float(line.split()[3]) 
1984              rmsd_err = float(line.split()[4]) 
1985   
1986              # Test if spectrum is a reference 
1987              if float(vcpmg) == 0.0: 
1988                  vcpmg = None 
1989              else: 
1990                  vcpmg = round(float(vcpmg), 3) 
1991   
1992              # Add ncyc to list 
1993              ncyclist.append(int(ncyc)) 
1994   
1995              # Set the current spectrum id 
1996              current_id = "Z_A%s"%(i) 
1997   
1998              # Set the current experiment type. 
1999              self.interpreter.relax_disp.exp_type(spectrum_id=current_id, exp_type='SQ CPMG') 
2000   
2001              # Set the peak intensity errors, as defined as the baseplane RMSD. 
2002              self.interpreter.spectrum.baseplane_rmsd(error=rmsd_err, spectrum_id=current_id) 
2003   
2004              # Set the NMR field strength of the spectrum. 
2005              self.interpreter.spectrometer.frequency(id=current_id, frq=set_sfrq, units='MHz') 
2006   
2007              # Relaxation dispersion CPMG constant time delay T (in s). 
2008              self.interpreter.relax_disp.relax_time(spectrum_id=current_id, time=time_T2) 
2009   
2010              # Set the relaxation dispersion CPMG frequencies. 
2011              self.interpreter.relax_disp.cpmg_setup(spectrum_id=current_id, cpmg_frq=vcpmg) 
2012   
2013              i += 1 
2014   
2015          # Specify the duplicated spectra. 
2016          self.interpreter.spectrum.replicated(spectrum_ids=['Z_A1', 'Z_A15']) 
2017   
2018          # Delete replicate spectrum 
2019          #self.interpreter.spectrum.delete('Z_A15') 
2020   
2021          MODELS = [MODEL_R2EFF, MODEL_NOREX] 
2022          GRID_INC = 5; MC_NUM = 3; MODSEL = 'AIC' 
2023   
2024          results_dir = ds.tmpdir 
2025   
2026          # Execute 
2027          relax_disp.Relax_disp(pipe_name='relax_disp', results_dir=results_dir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
2028   
2029          # Check spin less R2eff points. 
2030          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
2031              # Assert that spin 4, has one less R2eff point, since one of the intensities are negative. 
2032              if spin_id == ':4@N': 
2033                  self.assertEqual(len(cur_spin.r2eff), 14) 
2034              else: 
2035                  self.assertEqual(len(cur_spin.r2eff), 15) 
2036   
2037   
2038 -    def test_check_missing_r1(self): 
2039          """Test of the check_missing_r1() function.""" 
2040   
2041          # Set up some spins. 
2042          self.setup_missing_r1_spins() 
2043   
2044          # Set variables. 
2045          exp_type = 'R1rho' 
2046          frq = 800.1 * 1E6 
2047   
2048          spectrum_id='test' 
2049   
2050          # Set an experiment type to the pipe. 
2051          self.interpreter.relax_disp.exp_type(spectrum_id=spectrum_id, exp_type=exp_type) 
2052   
2053          # Set a frequency to loop through. 
2054          self.interpreter.spectrometer.frequency(id=spectrum_id, frq=frq, units='Hz') 
2055   
2056          # Check R1 for DPL94. 
2057          check_missing_r1_return = check_missing_r1(model=MODEL_DPL94) 
2058          self.assertEqual(check_missing_r1_return, True) 
2059   
2060          # Check R1 for R2eff. 
2061          check_missing_r1_return = check_missing_r1(model=MODEL_R2EFF) 
2062          self.assertEqual(check_missing_r1_return, False) 
2063   
2064          # The path to the data files. 
2065          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
2066   
2067          # Now load some R1 data. 
2068          self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
2069   
2070          # Check R1. 
2071          check_missing_r1_return = check_missing_r1(model=MODEL_DPL94) 
2072          self.assertEqual(check_missing_r1_return, False) 
2073   
2074   
2075 -    def test_cpmg_synthetic_b14_to_ns3d_cluster(self): 
2076          """Test synthetic cpmg data.  Created with B14, analysed with NS CPMG 2site 3D, for clustered analysis. 
2077   
2078          This is part of: U{Task #7807 <https://gna.org/task/index.php?7807>}: Speed-up of dispersion models for Clustered analysis. 
2079   
2080          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2081          """ 
2082   
2083          # Reset. 
2084          #self.interpreter.reset() 
2085   
2086          ## Set Experiments. 
2087          model_create = 'B14' 
2088          #model_create = 'NS CPMG 2-site expanded' 
2089          model_analyse = 'NS CPMG 2-site 3D' 
2090   
2091          # Exp 1 
2092          sfrq_1 = 599.8908617*1E6 
2093          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2094          time_T2_1 = 0.06 
2095          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2096          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2097          r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2098          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2099   
2100          sfrq_2 = 499.8908617*1E6 
2101          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2102          time_T2_2 = 0.05 
2103          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2104          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2105          r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2106          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2107   
2108          # Collect all exps 
2109          exps = [exp_1, exp_2] 
2110   
2111          spins = [ 
2112              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.95, 'dw': 2.} ], 
2113              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.95, 'dw': 1.} ] 
2114              ] 
2115   
2116          # Collect the data to be used. 
2117          ds.data = [model_create, model_analyse, spins, exps] 
2118   
2119          # The tmp directory. None is the local directory. 
2120          ds.tmpdir = ds.tmpdir 
2121   
2122          # The results directory. None is the local directory. 
2123          #ds.resdir = None 
2124          ds.resdir = ds.tmpdir 
2125   
2126          # Do r20_from_min_r2eff ?. 
2127          ds.r20_from_min_r2eff = True 
2128   
2129          # Remove insignificant level. 
2130          ds.insignificance = 0.0 
2131   
2132          # The grid search size (the number of increments per dimension). 
2133          ds.GRID_INC = None 
2134   
2135          # The do clustering. 
2136          ds.do_cluster = True 
2137   
2138          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2139          # The default value is 1e-25. 
2140          ds.set_func_tol = 1e-1 
2141   
2142          # The maximum number of iterations. 
2143          # The default value is 1e7. 
2144          ds.set_max_iter = 1000 
2145   
2146          # The verbosity level. 
2147          ds.verbosity = 1 
2148   
2149          # The rel_change WARNING level. 
2150          ds.rel_change = 0.05 
2151   
2152          # The plot_curves. 
2153          ds.plot_curves = False 
2154   
2155          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2156          ds.sherekhan_input = False 
2157   
2158          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2159          ds.opendx = False 
2160   
2161          # The set r2eff err. 
2162          ds.r2eff_err = 0.1 
2163   
2164          # The print result info. 
2165          ds.print_res = True 
2166   
2167          # Execute the script. 
2168          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2169   
2170          cur_spins = ds.data[2] 
2171          # Compare results. 
2172          for i in range(len(cur_spins)): 
2173              res_name, res_num, spin_name, params = cur_spins[i] 
2174              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2175              cur_spin = return_spin(cur_spin_id) 
2176   
2177              grid_params = ds.grid_results[i][3] 
2178   
2179              # Extract the clust results. 
2180              min_params = ds.clust_results[i][3] 
2181              # Now read the parameters. 
2182              print("For spin: '%s'"%cur_spin_id) 
2183              for mo_param in cur_spin.params: 
2184                  # The R2 is a dictionary, depending on spectrometer frequency. 
2185                  if isinstance(getattr(cur_spin, mo_param), dict): 
2186                      grid_r2 = grid_params[mo_param] 
2187                      min_r2 = min_params[mo_param] 
2188                      set_r2 = params[mo_param] 
2189                      for key, val in list(set_r2.items()): 
2190                          grid_r2_frq = grid_r2[key] 
2191                          min_r2_frq = min_r2[key] 
2192                          set_r2_frq = set_r2[key] 
2193                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2194                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2195                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2196                          if rel_change > ds.rel_change: 
2197                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2198                              print("###################################") 
2199   
2200                          ## Make test on R2. 
2201                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2202                  else: 
2203                      grid_val = grid_params[mo_param] 
2204                      min_val = min_params[mo_param] 
2205                      set_val = params[mo_param] 
2206                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2207                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2208                      if rel_change > ds.rel_change: 
2209                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2210                          print("###################################") 
2211   
2212                      ## Make test on parameters. 
2213                      if mo_param == 'dw': 
2214                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2215                      elif mo_param == 'kex': 
2216                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2217                      elif mo_param == 'pA': 
2218                          self.assertAlmostEqual(set_val, min_val, 2) 
2219   
2220   
2221 -    def test_cpmg_synthetic_b14_to_ns_star_cluster(self): 
2222          """Test synthetic cpmg data.  Created with B14, analysed with NS CPMG 2site STAR, for clustered analysis. 
2223   
2224          This is part of: U{Task #7807 <https://gna.org/task/index.php?7807>}: Speed-up of dispersion models for Clustered analysis. 
2225   
2226          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2227          """ 
2228   
2229          # Reset. 
2230          #self.interpreter.reset() 
2231   
2232          ## Set Experiments. 
2233          model_create = 'B14' 
2234          #model_create = 'NS CPMG 2-site expanded' 
2235          model_analyse = 'NS CPMG 2-site star' 
2236   
2237          # Exp 1 
2238          sfrq_1 = 599.8908617*1E6 
2239          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2240          time_T2_1 = 0.06 
2241          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2242          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2243          r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2244          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2245   
2246          sfrq_2 = 499.8908617*1E6 
2247          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2248          time_T2_2 = 0.05 
2249          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2250          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2251          r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2252          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2253   
2254          # Collect all exps 
2255          exps = [exp_1, exp_2] 
2256   
2257          spins = [ 
2258              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.95, 'dw': 2.} ], 
2259              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.95, 'dw': 1.} ] 
2260              ] 
2261   
2262          # Collect the data to be used. 
2263          ds.data = [model_create, model_analyse, spins, exps] 
2264   
2265          # The tmp directory. None is the local directory. 
2266          ds.tmpdir = ds.tmpdir 
2267   
2268          # The results directory. None is the local directory. 
2269          #ds.resdir = None 
2270          ds.resdir = ds.tmpdir 
2271   
2272          # Do r20_from_min_r2eff ?. 
2273          ds.r20_from_min_r2eff = True 
2274   
2275          # Remove insignificant level. 
2276          ds.insignificance = 0.0 
2277   
2278          # The grid search size (the number of increments per dimension). 
2279          ds.GRID_INC = None 
2280   
2281          # The do clustering. 
2282          ds.do_cluster = True 
2283   
2284          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2285          # The default value is 1e-25. 
2286          ds.set_func_tol = 1e-1 
2287   
2288          # The maximum number of iterations. 
2289          # The default value is 1e7. 
2290          ds.set_max_iter = 1000 
2291   
2292          # The verbosity level. 
2293          ds.verbosity = 1 
2294   
2295          # The rel_change WARNING level. 
2296          ds.rel_change = 0.05 
2297   
2298          # The plot_curves. 
2299          ds.plot_curves = False 
2300   
2301          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2302          ds.sherekhan_input = False 
2303   
2304          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2305          ds.opendx = False 
2306   
2307          # The set r2eff err. 
2308          ds.r2eff_err = 0.1 
2309   
2310          # The print result info. 
2311          ds.print_res = True 
2312   
2313          # Execute the script. 
2314          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2315   
2316          cur_spins = ds.data[2] 
2317          # Compare results. 
2318          for i in range(len(cur_spins)): 
2319              res_name, res_num, spin_name, params = cur_spins[i] 
2320              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2321              cur_spin = return_spin(cur_spin_id) 
2322   
2323              grid_params = ds.grid_results[i][3] 
2324   
2325              # Extract the clust results. 
2326              min_params = ds.clust_results[i][3] 
2327              # Now read the parameters. 
2328              print("For spin: '%s'"%cur_spin_id) 
2329              for mo_param in cur_spin.params: 
2330                  # The R2 is a dictionary, depending on spectrometer frequency. 
2331                  if isinstance(getattr(cur_spin, mo_param), dict): 
2332                      grid_r2 = grid_params[mo_param] 
2333                      min_r2 = min_params[mo_param] 
2334                      set_r2 = params[mo_param] 
2335                      for key, val in list(set_r2.items()): 
2336                          grid_r2_frq = grid_r2[key] 
2337                          min_r2_frq = min_r2[key] 
2338                          set_r2_frq = set_r2[key] 
2339                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2340                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2341                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2342                          if rel_change > ds.rel_change: 
2343                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2344                              print("###################################") 
2345   
2346                          ## Make test on R2. 
2347                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2348                  else: 
2349                      grid_val = grid_params[mo_param] 
2350                      min_val = min_params[mo_param] 
2351                      set_val = params[mo_param] 
2352                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2353                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2354                      if rel_change > ds.rel_change: 
2355                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2356                          print("###################################") 
2357   
2358                      ## Make test on parameters. 
2359                      if mo_param == 'dw': 
2360                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2361                      elif mo_param == 'kex': 
2362                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2363                      elif mo_param == 'pA': 
2364                          self.assertAlmostEqual(set_val, min_val, 2) 
2365   
2366   
2367 -    def test_cpmg_synthetic_ns3d_to_cr72(self): 
2368          """Test synthetic cpmg data. 
2369   
2370          This script will produce synthetic CPMG R2eff values according to the NS CPMG 2-site 3D model, and the fit the data with CR72. 
2371          """ 
2372   
2373          # Reset. 
2374          #self.interpreter.reset() 
2375   
2376          ## Set Experiments. 
2377          model_create = 'NS CPMG 2-site 3D' 
2378          #model_create = 'NS CPMG 2-site expanded' 
2379          model_analyse = 'CR72' 
2380          # Exp 1 
2381          sfrq_1 = 599.8908617*1E6 
2382          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2383          time_T2_1 = 0.06 
2384          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2385          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2386          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2387   
2388          sfrq_2 = 499.8908617*1E6 
2389          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2390          time_T2_2 = 0.05 
2391          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2392          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2393          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2394   
2395          # Collect all exps 
2396          exps = [exp_1, exp_2] 
2397   
2398          spins = [ 
2399              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:10.}, 'r2a': {r20_key_1:10., r20_key_2:10.}, 'r2b': {r20_key_1:10., r20_key_2:10.}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ] 
2400              ] 
2401   
2402          # Collect the data to be used. 
2403          ds.data = [model_create, model_analyse, spins, exps] 
2404   
2405          # The tmp directory. None is the local directory. 
2406          ds.tmpdir = ds.tmpdir 
2407   
2408          # The results directory. None is the local directory. 
2409          #ds.resdir = None 
2410          ds.resdir = ds.tmpdir 
2411   
2412          # Do r20_from_min_r2eff ?. 
2413          ds.r20_from_min_r2eff = True 
2414   
2415          # Remove insignificant level. 
2416          ds.insignificance = 0.0 
2417   
2418          # The grid search size (the number of increments per dimension). 
2419          ds.GRID_INC = 8 
2420   
2421          # The do clustering. 
2422          ds.do_cluster = False 
2423   
2424          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2425          # The default value is 1e-25. 
2426          ds.set_func_tol = 1e-9 
2427   
2428          # The maximum number of iterations. 
2429          # The default value is 1e7. 
2430          ds.set_max_iter = 1000 
2431   
2432          # The verbosity level. 
2433          ds.verbosity = 1 
2434   
2435          # The rel_change WARNING level. 
2436          ds.rel_change = 0.05 
2437   
2438          # The plot_curves. 
2439          ds.plot_curves = False 
2440   
2441          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2442          ds.sherekhan_input = False 
2443   
2444          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2445          ds.opendx = False 
2446   
2447          # The set r2eff err. 
2448          ds.r2eff_err = 0.1 
2449   
2450          # The print result info. 
2451          ds.print_res = False 
2452   
2453          # Execute the script. 
2454          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2455   
2456          cur_spins = ds.data[2] 
2457          # Compare results. 
2458          for i in range(len(cur_spins)): 
2459              res_name, res_num, spin_name, params = cur_spins[i] 
2460              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2461              cur_spin = return_spin(cur_spin_id) 
2462   
2463              grid_params = ds.grid_results[i][3] 
2464              min_params = ds.min_results[i][3] 
2465              # Now read the parameters. 
2466              print("For spin: '%s'"%cur_spin_id) 
2467              for mo_param in cur_spin.params: 
2468                  # The R2 is a dictionary, depending on spectrometer frequency. 
2469                  if isinstance(getattr(cur_spin, mo_param), dict): 
2470                      grid_r2 = grid_params[mo_param] 
2471                      min_r2 = min_params[mo_param] 
2472                      set_r2 = params[mo_param] 
2473                      for key, val in list(set_r2.items()): 
2474                          grid_r2_frq = grid_r2[key] 
2475                          min_r2_frq = min_r2[key] 
2476                          set_r2_frq = set_r2[key] 
2477                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2478                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2479                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2480                          if rel_change > ds.rel_change: 
2481                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2482                              print("###################################") 
2483   
2484                          ## Make test on R2. 
2485                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 2) 
2486                  else: 
2487                      grid_val = grid_params[mo_param] 
2488                      min_val = min_params[mo_param] 
2489                      set_val = params[mo_param] 
2490                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2491                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2492                      if rel_change > ds.rel_change: 
2493                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2494                          print("###################################") 
2495   
2496                      ## Make test on parameters. 
2497                      if mo_param == 'dw': 
2498                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2499                      elif mo_param == 'kex': 
2500                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2501                      elif mo_param == 'pA': 
2502                          self.assertAlmostEqual(set_val, min_val, 3) 
2503   
2504   
2505 -    def test_cpmg_synthetic_ns3d_to_b14(self): 
2506          """Test synthetic cpmg data. 
2507   
2508          This script will produce synthetic CPMG R2eff values according to the NS CPMG 2-site 3D model, and the fit the data with B14. 
2509          Try to catch bug #22021 U{https://gna.org/bugs/index.php?22021}: Model B14 shows bad fitting to data. 
2510          """ 
2511   
2512          # Reset. 
2513          #self.interpreter.reset() 
2514   
2515          ## Set Experiments. 
2516          model_create = 'NS CPMG 2-site 3D' 
2517          #model_create = 'NS CPMG 2-site expanded' 
2518          model_analyse = 'B14' 
2519          # Exp 1 
2520          sfrq_1 = 599.8908617*1E6 
2521          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2522          time_T2_1 = 0.06 
2523          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2524          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2525          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2526   
2527          sfrq_2 = 499.8908617*1E6 
2528          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2529          time_T2_2 = 0.05 
2530          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2531          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2532          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2533   
2534          # Collect all exps 
2535          exps = [exp_1, exp_2] 
2536   
2537          spins = [ 
2538              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:10.}, 'r2a': {r20_key_1:10., r20_key_2:10.}, 'r2b': {r20_key_1:10., r20_key_2:10.}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ] 
2539              ] 
2540   
2541          # Collect the data to be used. 
2542          ds.data = [model_create, model_analyse, spins, exps] 
2543   
2544          # The tmp directory. None is the local directory. 
2545          ds.tmpdir = ds.tmpdir 
2546   
2547          # The results directory. None is the local directory. 
2548          #ds.resdir = None 
2549          ds.resdir = ds.tmpdir 
2550   
2551          # Do r20_from_min_r2eff ?. 
2552          ds.r20_from_min_r2eff = True 
2553   
2554          # Remove insignificant level. 
2555          ds.insignificance = 0.0 
2556   
2557          # The grid search size (the number of increments per dimension). 
2558          ds.GRID_INC = 8 
2559   
2560          # The do clustering. 
2561          ds.do_cluster = False 
2562   
2563          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2564          # The default value is 1e-25. 
2565          ds.set_func_tol = 1e-9 
2566   
2567          # The maximum number of iterations. 
2568          # The default value is 1e7. 
2569          ds.set_max_iter = 1000 
2570   
2571          # The verbosity level. 
2572          ds.verbosity = 1 
2573   
2574          # The rel_change WARNING level. 
2575          ds.rel_change = 0.05 
2576   
2577          # The plot_curves. 
2578          ds.plot_curves = False 
2579   
2580          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2581          ds.sherekhan_input = False 
2582   
2583          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2584          ds.opendx = False 
2585   
2586          # The set r2eff err. 
2587          ds.r2eff_err = 0.1 
2588   
2589          # The print result info. 
2590          ds.print_res = False 
2591   
2592          # Execute the script. 
2593          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2594   
2595          cur_spins = ds.data[2] 
2596          # Compare results. 
2597          for i in range(len(cur_spins)): 
2598              res_name, res_num, spin_name, params = cur_spins[i] 
2599              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2600              cur_spin = return_spin(cur_spin_id) 
2601   
2602              grid_params = ds.grid_results[i][3] 
2603              min_params = ds.min_results[i][3] 
2604              # Now read the parameters. 
2605              print("For spin: '%s'"%cur_spin_id) 
2606              for mo_param in cur_spin.params: 
2607                  # The R2 is a dictionary, depending on spectrometer frequency. 
2608                  if isinstance(getattr(cur_spin, mo_param), dict): 
2609                      grid_r2 = grid_params[mo_param] 
2610                      min_r2 = min_params[mo_param] 
2611                      set_r2 = params[mo_param] 
2612                      for key, val in list(set_r2.items()): 
2613                          grid_r2_frq = grid_r2[key] 
2614                          min_r2_frq = min_r2[key] 
2615                          set_r2_frq = set_r2[key] 
2616                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2617                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2618                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2619                          if rel_change > ds.rel_change: 
2620                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2621                              print("###################################") 
2622   
2623                          ## Make test on R2. 
2624                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 2) 
2625                  else: 
2626                      grid_val = grid_params[mo_param] 
2627                      min_val = min_params[mo_param] 
2628                      set_val = params[mo_param] 
2629                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2630                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2631                      if rel_change > ds.rel_change: 
2632                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2633                          print("###################################") 
2634   
2635                      ## Make test on parameters. 
2636                      if mo_param == 'dw': 
2637                          self.assertAlmostEqual(set_val/10, min_val/10, 5) 
2638                      elif mo_param == 'kex': 
2639                          self.assertAlmostEqual(set_val/1000, min_val/1000, 5) 
2640                      elif mo_param == 'pA': 
2641                          self.assertAlmostEqual(set_val, min_val, 6) 
2642   
2643   
2644 -    def test_cpmg_synthetic_ns3d_to_cr72_noise_cluster(self): 
2645          """Test synthetic cpmg data. For CR72 with small noise and cluster. 
2646   
2647          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2648          """ 
2649   
2650          # Reset. 
2651          #self.interpreter.reset() 
2652   
2653          ## Set Experiments. 
2654          model_create = 'NS CPMG 2-site 3D' 
2655          #model_create = 'NS CPMG 2-site expanded' 
2656          model_analyse = 'CR72' 
2657   
2658          # Exp 1 
2659          sfrq_1 = 599.8908617*1E6 
2660          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2661          time_T2_1 = 0.06 
2662          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2663          r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2664          #r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2665          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2666   
2667          sfrq_2 = 499.8908617*1E6 
2668          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2669          time_T2_2 = 0.05 
2670          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2671          r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2672          #r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2673          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2674   
2675          # Collect all exps 
2676          exps = [exp_1, exp_2] 
2677   
2678          spins = [ 
2679              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ], 
2680              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.99, 'dw': 1.} ] 
2681              ] 
2682   
2683          # Collect the data to be used. 
2684          ds.data = [model_create, model_analyse, spins, exps] 
2685   
2686          # The tmp directory. None is the local directory. 
2687          ds.tmpdir = ds.tmpdir 
2688   
2689          # The results directory. None is the local directory. 
2690          #ds.resdir = None 
2691          ds.resdir = ds.tmpdir 
2692   
2693          # Do r20_from_min_r2eff ?. 
2694          ds.r20_from_min_r2eff = True 
2695   
2696          # Remove insignificant level. 
2697          ds.insignificance = 0.0 
2698   
2699          # The grid search size (the number of increments per dimension). 
2700          ds.GRID_INC = 13 
2701   
2702          # The do clustering. 
2703          ds.do_cluster = True 
2704   
2705          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2706          # The default value is 1e-25. 
2707          ds.set_func_tol = 1e-8 
2708   
2709          # The maximum number of iterations. 
2710          # The default value is 1e7. 
2711          ds.set_max_iter = 10000 
2712   
2713          # The verbosity level. 
2714          ds.verbosity = 1 
2715   
2716          # The rel_change WARNING level. 
2717          ds.rel_change = 0.05 
2718   
2719          # The plot_curves. 
2720          ds.plot_curves = False 
2721   
2722          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2723          ds.sherekhan_input = False 
2724   
2725          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2726          ds.opendx = False 
2727   
2728          # The set r2eff err. 
2729          ds.r2eff_err = 0.1 
2730   
2731          # The print result info. 
2732          ds.print_res = False 
2733   
2734          # Execute the script. 
2735          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2736   
2737          cur_spins = ds.data[2] 
2738          # Compare results. 
2739          for i in range(len(cur_spins)): 
2740              res_name, res_num, spin_name, params = cur_spins[i] 
2741              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2742              cur_spin = return_spin(cur_spin_id) 
2743   
2744              grid_params = ds.grid_results[i][3] 
2745   
2746              # Extract the clust results. 
2747              min_params = ds.clust_results[i][3] 
2748              # Now read the parameters. 
2749              print("For spin: '%s'"%cur_spin_id) 
2750              for mo_param in cur_spin.params: 
2751                  # The R2 is a dictionary, depending on spectrometer frequency. 
2752                  if isinstance(getattr(cur_spin, mo_param), dict): 
2753                      grid_r2 = grid_params[mo_param] 
2754                      min_r2 = min_params[mo_param] 
2755                      set_r2 = params[mo_param] 
2756                      for key, val in list(set_r2.items()): 
2757                          grid_r2_frq = grid_r2[key] 
2758                          min_r2_frq = min_r2[key] 
2759                          set_r2_frq = set_r2[key] 
2760                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2761                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2762                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2763                          if rel_change > ds.rel_change: 
2764                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2765                              print("###################################") 
2766   
2767                          ## Make test on R2. 
2768                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2769                  else: 
2770                      grid_val = grid_params[mo_param] 
2771                      min_val = min_params[mo_param] 
2772                      set_val = params[mo_param] 
2773                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2774                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2775                      if rel_change > ds.rel_change: 
2776                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2777                          print("###################################") 
2778   
2779                      ## Make test on parameters. 
2780                      if mo_param == 'dw': 
2781                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2782                      elif mo_param == 'kex': 
2783                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2784                      elif mo_param == 'pA': 
2785                          self.assertAlmostEqual(set_val, min_val, 2) 
2786   
2787   
2788 -    def test_cpmg_synthetic_dx_map_points(self): 
2789          """Test synthetic cpmg data, calling the dx.map function with one or two points. 
2790   
2791          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2792          """ 
2793   
2794          # Reset. 
2795          #self.interpreter.reset() 
2796   
2797          ## Set Experiments. 
2798          model_create = MODEL_NS_CPMG_2SITE_EXPANDED 
2799          model_analyse = 'CR72' 
2800          # Exp 1 
2801          sfrq_1 = 599.8908617*1E6 
2802          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2803          time_T2_1 = 0.06 
2804          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2805          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2806          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2807   
2808          sfrq_2 = 499.8908617*1E6 
2809          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2810          time_T2_2 = 0.05 
2811          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2812          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2813          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2814   
2815          # Collect all exps 
2816          exps = [exp_1, exp_2] 
2817   
2818          spins = [ 
2819              ['Ala', 1, 'N', {'r2': {r20_key_1:2, r20_key_2:2}, 'r2a': {r20_key_1:2, r20_key_2:2}, 'r2b': {r20_key_1:2, r20_key_2:2}, 'kex': 1000, 'pA': 0.99, 'dw': 2} ] 
2820              ] 
2821   
2822          # Collect the data to be used. 
2823          ds.data = [model_create, model_analyse, spins, exps] 
2824   
2825          # The tmp directory. None is the local directory. 
2826          ds.tmpdir = ds.tmpdir 
2827   
2828          # The results directory. None is the local directory. 
2829          #ds.resdir = None 
2830          ds.resdir = ds.tmpdir 
2831   
2832          # Do r20_from_min_r2eff ?. 
2833          ds.r20_from_min_r2eff = True 
2834   
2835          # Remove insignificant level. 
2836          ds.insignificance = 0.0 
2837   
2838          # The grid search size (the number of increments per dimension). 
2839          ds.GRID_INC = None 
2840   
2841          # The do clustering. 
2842          ds.do_cluster = False 
2843   
2844          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2845          # The default value is 1e-25. 
2846          ds.set_func_tol = 1e-9 
2847   
2848          # The maximum number of iterations. 
2849          # The default value is 1e7. 
2850          ds.set_max_iter = 1000 
2851   
2852          # The verbosity level. 
2853          ds.verbosity = 1 
2854   
2855          # The rel_change WARNING level. 
2856          ds.rel_change = 0.05 
2857   
2858          # The plot_curves. 
2859          ds.plot_curves = False 
2860   
2861          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2862          ds.sherekhan_input = False 
2863   
2864          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2865          ds.opendx = False 
2866   
2867          # The set r2eff err. 
2868          ds.r2eff_err = 0.1 
2869   
2870          # The print result info. 
2871          ds.print_res = False 
2872   
2873          # Execute the script. 
2874          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2875   
2876          # Get the spins. 
2877          cur_spins = ds.data[2] 
2878   
2879          # First switch pipe, since dx.map will go through parameters and end up a "bad" place. :-) 
2880          ds.pipe_name_MODEL_MAP = "%s_%s_map"%(ds.pipe_name, model_analyse) 
2881          self.interpreter.pipe.copy(pipe_from=ds.pipe_name, pipe_to=ds.pipe_name_MODEL_MAP, bundle_to = ds.pipe_bundle) 
2882          self.interpreter.pipe.switch(pipe_name=ds.pipe_name_MODEL_MAP) 
2883   
2884          # Copy R2eff, but not the original parameters 
2885          self.interpreter.value.copy(pipe_from=ds.pipe_name_r2eff, pipe_to=ds.pipe_name_MODEL_MAP, param='r2eff') 
2886   
2887          # Then select model. 
2888          self.interpreter.relax_disp.select_model(model=model_analyse) 
2889   
2890          # Define dx.map settings. 
2891          ds.dx_inc = 4 
2892          ds.dx_params = ['dw', 'pA', 'kex'] 
2893   
2894          res_name, res_num, spin_name, params = cur_spins[0] 
2895          cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2896          cur_spin = return_spin(cur_spin_id) 
2897   
2898          print("Params for dx map is") 
2899          print(ds.dx_params) 
2900          print("Point param for dx map is") 
2901          print(ds.dx_set_val) 
2902          cur_model = model_analyse.replace(' ', '_') 
2903          file_name_map = "%s_map%s" % (cur_model, cur_spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
2904          file_name_point = "%s_point%s" % (cur_model, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) 
2905          self.interpreter.dx.map(params=ds.dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=ds.dx_inc, lower=None, upper=None, axis_incs=10, file_prefix=file_name_map, dir=ds.resdir, point=[ds.dx_set_val, ds.dx_clust_val], point_file=file_name_point, create_par_file=True) 
2906   
2907          ## Check for file creation 
2908          # Set filepaths. 
2909          map_cfg = ds.tmpdir+sep+file_name_map+".cfg" 
2910          map_net = ds.tmpdir+sep+file_name_map+".net" 
2911          map_general = ds.tmpdir+sep+file_name_map+".general" 
2912          map_par = get_file_path(file_name=file_name_map+".par", dir=ds.tmpdir) 
2913          map_plot = get_file_path(file_name=file_name_map+".py", dir=ds.tmpdir) 
2914   
2915          point_general = ds.tmpdir+sep+file_name_point+".general" 
2916          point_point = ds.tmpdir+sep+file_name_point 
2917          point_par = get_file_path(file_name=file_name_point+".par", dir=ds.tmpdir) 
2918   
2919          # Test the files exists. 
2920          self.assert_(access(map_cfg, F_OK)) 
2921          self.assert_(access(map_net, F_OK)) 
2922          self.assert_(access(map_general, F_OK)) 
2923          self.assert_(access(map_par, F_OK)) 
2924          self.assert_(access(map_plot, F_OK)) 
2925          self.assert_(access(point_general, F_OK)) 
2926          self.assert_(access(point_point, F_OK)) 
2927          self.assert_(access(point_par, F_OK)) 
2928   
2929          # Open the files for testing. 
2930          # Check the cfg file. 
2931          print("\nChecking the dx map .cfg file.") 
2932          res_file = [ 
2933              '//'+"\n", 
2934              '//'+"\n", 
2935              '// time: Thu May  8 18:55:31 2014'+"\n", 
2936              '//'+"\n", 
2937              '// version: 3.2.0 (format), 4.3.2 (DX)'+"\n", 
2938              '//'+"\n", 
2939              '//'+"\n", 
2940              '// panel[0]: position = (0.0164,0.0000), size = 0.2521x0.1933, startup = 1, devstyle = 1'+"\n", 
2941              '// title: value = Control Panel'+"\n", 
2942              '//'+"\n", 
2943              '// workspace: width = 251, height = 142'+"\n", 
2944              '// layout: snap = 0, width = 50, height = 50, align = NN'+"\n", 
2945              '//'+"\n", 
2946              '// interactor Selector[1]: num_components = 1, value = 1 '+"\n", 
2947              '// selections: maximum = 2, current = 0 '+"\n", 
2948              '// option[0]: name = "Colour", value = 1'+"\n", 
2949              '// option[1]: name = "Grey", value = 2'+"\n", 
2950              '// instance: panel = 0, x = 81, y = 6, style = Scrolled List, vertical = 1, size = 170x136'+"\n", 
2951              '// label: value = Colour Selector'+"\n", 
2952              '//'+"\n", 
2953              '// node Image[3]:'+"\n", 
2954              '// title: value = Surface'+"\n", 
2955              '// depth: value = 24'+"\n", 
2956              '// window: position = (0.0000,0.0400), size = 0.9929x0.9276'+"\n", 
2957          ] 
2958          file = open(map_cfg, 'r') 
2959          lines = file.readlines() 
2960          file.close() 
2961          for i in range(len(res_file)): 
2962              # Skip time point 
2963              if i == 2: 
2964                  continue 
2965              self.assertEqual(res_file[i], lines[i]) 
2966   
2967          print("\nChecking the dx map .general file.") 
2968          res_file = [ 
2969              'file = CR72_map_1_N'+"\n", 
2970              'grid = 5 x 5 x 5'+"\n", 
2971              'format = ascii'+"\n", 
2972              'interleaving = field'+"\n", 
2973              'majority = row'+"\n", 
2974              'field = data'+"\n", 
2975              'structure = scalar'+"\n", 
2976              'type = float'+"\n", 
2977              'dependency = positions'+"\n", 
2978              'positions = regular, regular, regular, 0, 1, 0, 1, 0, 1'+"\n", 
2979              ''+"\n", 
2980              'end'+"\n", 
2981          ] 
2982          file = open(map_general, 'r') 
2983          lines = file.readlines() 
2984          file.close() 
2985          for i in range(len(res_file)): 
2986              # Skip time point 
2987              #if i == 2: 
2988              #    continue 
2989              self.assertEqual(res_file[i], lines[i]) 
2990   
2991          print("\nChecking the dx point .general file.") 
2992          res_file = [ 
2993              'file = CR72_point_1_N'+"\n", 
2994              'points = 2'+"\n", 
2995              'format = ascii'+"\n", 
2996              'interleaving = field'+"\n", 
2997              'field = locations, field0'+"\n", 
2998              'structure = 3-vector, scalar'+"\n", 
2999              'type = float, float'+"\n", 
3000              ''+"\n", 
3001              'end'+"\n", 
3002          ] 
3003          file = open(point_general, 'r') 
3004          lines = file.readlines() 
3005          file.close() 
3006          for i in range(len(res_file)): 
3007              # Skip time point 
3008              #if i == 2: 
3009              #    continue 
3010              self.assertEqual(res_file[i], lines[i]) 
3011   
3012          print("\nChecking the dx point point file.") 
3013          res_file = [ 
3014              '0.8            3.92           0.39964        1'+"\n", 
3015              '0.76981        3.9169         0.41353        1'+"\n", 
3016          ] 
3017          file = open(point_point, 'r') 
3018          lines = file.readlines() 
3019          file.close() 
3020          for i in range(len(res_file)): 
3021              # Skip time point 
3022              #if i == 2: 
3023              #    continue 
3024              self.assertEqual(res_file[i], lines[i]) 
3025   
3026          print("\nChecking the dx point par file.") 
3027          res_file = [ 
3028              '# i    dw         pA         kex           chi2          i_sort    dw_sort    pA_sort    kex_sort      chi2_sort     '+"\n", 
3029              '0      2.00000    0.99000    1000.00000    6185.84926    0         2.00000    0.99000    1000.00000    6185.84926    '+"\n", 
3030              '1      1.92453    0.98961    1034.72206    6396.02770    1         1.92453    0.98961    1034.72206    6396.02770    '+"\n", 
3031          ] 
3032          res_file2 = [ 
3033              '# i    dw         pA         kex           chi2          i_sort    dw_sort    pA_sort    kex_sort      chi2_sort     '+"\n", 
3034              '0      2.00000    0.99000    1000.00000    6185.84926    0         2.00000    0.99000    1000.00000    6185.84926    '+"\n", 
3035              '1      1.92452    0.98961    1034.72424    6396.02439    1         1.92452    0.98961    1034.72424    6396.02439    '+"\n", 
3036          ]  # Python 2.5 and 3.1. 
3037          file = open(point_par, 'r') 
3038          lines = file.readlines() 
3039          file.close() 
3040          for i in range(len(res_file)): 
3041              if lines[i] != res_file[i] and lines[i] != res_file2[i]: 
3042                  self.assertEqual(res_file[i], lines[i]) 
3043   
3044          print("\nChecking the matplotlib surface plot file.") 
3045          res_file = [ 
3046              'from copy import deepcopy'+"\n", 
3047              'import numpy as np'+"\n", 
3048              'import scipy.interpolate'+"\n", 
3049              'from numpy.ma import masked_where'+"\n", 
3050              ''+"\n", 
3051              'from mpl_toolkits.mplot3d import axes3d'+"\n", 
3052              'import matplotlib.pyplot as plt'+"\n", 
3053              'from matplotlib import cm'+"\n", 
3054              ''+"\n", 
3055              '# Open file and get header.'+"\n", 
3056              'mapfile_name = "%s.par"'%file_name_map+"\n", 
3057              'pointfile_name = "%s.par"'%file_name_point+"\n", 
3058              ''+"\n", 
3059          ] 
3060          file = open(map_plot, 'r') 
3061          lines = file.readlines() 
3062          file.close() 
3063          for i in range(len(res_file)): 
3064              self.assertEqual(res_file[i], lines[i]) 
3065   
3066   
3067 -    def test_curve_type_cpmg_fixed_time(self): 
3068          """Test the curve type detection using the Dr. Flemming Hansen's CPMG fixed time test data.""" 
3069   
3070          # Reset. 
3071          self.interpreter.reset() 
3072   
3073          # Load the base data. 
3074          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
3075          self.interpreter.state.load(data_path+sep+'r2eff_values') 
3076   
3077          # The type. 
3078          curve_type = get_curve_type(id='500_133.33.in') 
3079          self.assertEqual(curve_type, 'fixed time') 
3080   
3081   
3082 -    def test_curve_type_r1rho_exponential(self, model=None): 
3083          """Test the curve type detection using the 'M61' exponential test data.""" 
3084   
3085          # Reset. 
3086          self.interpreter.reset() 
3087   
3088          # Load the base data. 
3089          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_on_res_m61' 
3090          self.interpreter.state.load(data_path+sep+'r2eff_values') 
3091   
3092          # The type. 
3093          curve_type = get_curve_type(id='nu_2000_ncyc9') 
3094          self.assertEqual(curve_type, 'exponential') 
3095   
3096   
3097 -    def test_curve_type_r1rho_fixed_time(self, model=None): 
3098          """Test the curve type detection using the 'TP02' fixed time test data.""" 
3099   
3100          # Reset. 
3101          self.interpreter.reset() 
3102   
3103          # Load the base data. 
3104          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02' 
3105          self.interpreter.state.load(data_path+sep+'r2eff_values') 
3106   
3107          # The type. 
3108          curve_type = get_curve_type(id='nu_1000.0_500MHz') 
3109          self.assertEqual(curve_type, 'fixed time') 
3110   
3111   
3112 -    def test_dpl94_data_to_dpl94(self): 
3113          """Test the relaxation dispersion 'DPL94' model curve fitting to fixed time synthetic data.""" 
3114   
3115          # Fixed time variable. 
3116          ds.fixed = True 
3117   
3118          # Execute the script. 
3119          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_dpl94.py') 
3120   
3121          # The original parameters. 
3122          i0 = [100000.0, 20000.0] 
3123          r1rho_prime = [2.25, 24.0] 
3124          pA = 0.7 
3125          kex = 1000.0 
3126          delta_omega = [1.0, 2.0] 
3127          phi_ex = [] 
3128          for i in range(2): 
3129              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
3130   
3131          # Switch to the 'DPL94' model data pipe, then check for each spin. 
3132          self.interpreter.pipe.switch('DPL94 - relax_disp') 
3133          spin_index = 0 
3134          for spin, spin_id in spin_loop(return_id=True): 
3135              # Printout. 
3136              print("\nSpin %s." % spin_id) 
3137   
3138              # Check the fitted parameters. 
3139              self.assertAlmostEqual(spin.r2['R1rho - 800.00000000 MHz']/10, r1rho_prime[spin_index]/10, 2) 
3140              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
3141              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
3142   
3143              # Increment the spin index. 
3144              spin_index += 1 
3145   
3146   
3147 -    def test_dx_map_clustered(self): 
3148          """Test making dx_map for residues under clustered calculation. 
3149   
3150          This uses CPMG data from: 
3151              - Webb H, Tynan-Connolly BM, Lee GM, Farrell D, O'Meara F, Soendergaard CR, Teilum K, Hewage C, McIntosh LP, Nielsen JE 
3152                Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations. 
3153                (2011), Proteins: Struct, Funct, Bioinf 79(3):685-702, U{DOI 10.1002/prot.22886<http://dx.doi.org/10.1002/prot.22886>} 
3154          """ 
3155   
3156          # Define path to data  
3157          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'HWebb_KTeilum_Proteins_Struct_Funct_Bioinf_2011' 
3158   
3159          # Read data. 
3160          self.interpreter.results.read(prev_data_path + sep + 'FT_-_CR72_-_min_-_128_-_free_spins') 
3161   
3162          # Get residue of interest. 
3163          cur_spin_id = ":%i@%s"%(52, 'N') 
3164          cur_spin_id_str = cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_') 
3165   
3166          # Get the spin container. 
3167          cur_spin = return_spin(cur_spin_id) 
3168   
3169          # Get the chi2 value 
3170          pre_chi2 = cur_spin.chi2 
3171   
3172          # Then do a local minimisation. 
3173          #self.interpreter.select.spin(":%i@%s"%(2, 'N')) 
3174          self.interpreter.minimise.calculate() 
3175   
3176          # Get the chi2 value after calculation. 
3177          calc_chi2 = cur_spin.chi2 
3178   
3179          # Assert calculation is equal. 
3180          self.assertAlmostEqual(pre_chi2, calc_chi2) 
3181   
3182          # Define dx.map settings. 
3183          dx_inc = 2 
3184          dx_inc_sides = dx_inc / 2 
3185   
3186          dx_params = ['dw', 'pA', 'kex'] 
3187          dx_point_clustered_min = [cur_spin.dw, cur_spin.pA, cur_spin.kex] 
3188   
3189          print("Params for dx map is") 
3190          print(dx_params) 
3191          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3192          print(dx_point_clustered_min) 
3193   
3194          # Define file_names. 
3195          cur_model = 'CR72' 
3196          file_name_map = "%s_map%s" % (cur_model, cur_spin_id_str) 
3197          file_name_point = "%s_point%s" % (cur_model, cur_spin_id_str) 
3198   
3199          # Step-size of parameter is 10 % 
3200          param_delta = 0.1 
3201   
3202          # Determine bounds for lower and upper 
3203          lower = [] 
3204          upper = [] 
3205          for i, param_val in enumerate(dx_point_clustered_min): 
3206              param = dx_params[i] 
3207              step_val = param_delta * param_val 
3208              step_length = step_val * dx_inc_sides 
3209   
3210              # Calculate value 
3211              low_val = param_val - step_length 
3212              lower.append(low_val) 
3213   
3214              upp_val = param_val + step_length 
3215              upper.append(upp_val) 
3216   
3217              print("For param %s, lower=%3.3f, upper=%3.3f, step_value=%3.3f, steps=%i, centered at=%3.3f"% (param, low_val, upp_val, step_val, dx_inc, param_val)) 
3218   
3219          # If the number of increments are 2, there will be 3 point calculations per parameter. 
3220          # Since we have ordered the lower and upper limits on sides of the parameter, the middle index should give us the expected global value. 
3221          dx_param_indexes = dx_inc + 1 
3222          dx_point_index = dx_inc_sides + 1 
3223   
3224          # Find the line number. 
3225          line = 1 
3226          for i in range(1, dx_param_indexes + 1): 
3227              for j in range(1, dx_param_indexes + 1): 
3228                  for k in range(1, dx_param_indexes + 1): 
3229                      if i == dx_point_index and j == dx_point_index and k == dx_point_index: 
3230                          line_chi2 = line 
3231                      # Add to line counter. 
3232                      line += 1 
3233   
3234          # Define temporary folder. 
3235          result_dir = self.tmpdir 
3236   
3237          # For testing. 
3238          #result_dir = None 
3239          #lower = None 
3240          #upper = None 
3241          #self.interpreter.relax_disp.cluster(cluster_id='free spins', spin_id=cur_spin_id) 
3242   
3243   
3244          # Then do the map. 
3245          self.interpreter.dx.map(params=dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=dx_inc, lower=lower, upper=upper, axis_incs=10, file_prefix=file_name_map, dir=result_dir, point=dx_point_clustered_min, point_file=file_name_point) 
3246   
3247          # Print where to locate values. 
3248          nr_chi2_val = dx_param_indexes**3 
3249          print("Nr of chi2 calculations are=%i"%nr_chi2_val) 
3250          print("Global chi2=%3.3f, Calc_chi=%3.3f, map_line_chi2=%i" % (pre_chi2, calc_chi2, line_chi2) ) 
3251   
3252          ## Check for file creation 
3253          # Set filepaths. 
3254          map_name = get_file_path(file_name=file_name_map, dir=result_dir) 
3255          map_cfg = get_file_path(file_name=file_name_map+".cfg", dir=result_dir) 
3256          map_net = get_file_path(file_name=file_name_map+".net", dir=result_dir) 
3257          map_general = get_file_path(file_name=file_name_map+".general", dir=result_dir) 
3258   
3259          point_general = get_file_path(file_name=file_name_point+".general", dir=result_dir) 
3260          point_point = get_file_path(file_name=file_name_point, dir=result_dir) 
3261   
3262          # Test the files exists. 
3263          self.assert_(access(map_cfg, F_OK)) 
3264          self.assert_(access(map_net, F_OK)) 
3265          self.assert_(access(map_general, F_OK)) 
3266          self.assert_(access(point_general, F_OK)) 
3267          self.assert_(access(point_point, F_OK)) 
3268   
3269          # Open the file, and assert the chi2 value is as expected. 
3270          get_data = extract_data(file=map_name) 
3271   
3272          # Extract line 0, column 0. 
3273          test = float(get_data[line_chi2-1][0]) 
3274   
3275          # Assert. 
3276          self.assertAlmostEqual(test, pre_chi2,  6) 
3277   
3278   
3279 -    def test_dx_map_clustered_create_par_file(self): 
3280          """Test making dx_map for residues under clustered calculation, and the creation of the parameter file. 
3281   
3282          U{Task #7860<https://gna.org/task/index.php?7860>} : When dx_map is issued, create a parameter file which maps parameters to chi2 value. 
3283   
3284          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
3285          """ 
3286   
3287          # Define path to data  
3288          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+'surface_chi2_clustered_fitting' 
3289   
3290          # Read data. 
3291          self.interpreter.results.read(prev_data_path + sep + 'coMDD_-_TSMFK01_-_min_-_32_-_free_spins.bz2') 
3292   
3293          # Get residue of interest. 
3294          cur_spin_id = ":%i@%s"%(65, 'N') 
3295          cur_spin_id_str = cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_') 
3296   
3297          # Get the spin container. 
3298          cur_spin = return_spin(cur_spin_id) 
3299   
3300          # Get the chi2 value 
3301          pre_chi2 = cur_spin.chi2 
3302   
3303          # Then do a local minimisation. 
3304          #self.interpreter.select.spin(":%i@%s"%(2, 'N')) 
3305          self.interpreter.minimise.calculate() 
3306   
3307          # Get the chi2 value after calculation. 
3308          calc_chi2 = cur_spin.chi2 
3309   
3310          # Assert calculation is equal. 
3311          self.assertAlmostEqual(pre_chi2, calc_chi2) 
3312   
3313          # Define dx.map settings. 
3314          dx_inc = 2 
3315          dx_params = ['dw', 'k_AB', 'r2a'] 
3316          dx_point_clustered_min = [cur_spin.dw, cur_spin.k_AB, cur_spin.r2a['SQ CPMG - 499.86214000 MHz']] 
3317   
3318          print("Params for dx map is") 
3319          print(dx_params) 
3320          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3321          print(dx_point_clustered_min) 
3322   
3323          # Define file_names. 
3324          cur_model = 'TSMFK01' 
3325          file_name_map = "%s_map%s" % (cur_model, cur_spin_id_str) 
3326          file_name_point = "%s_point%s" % (cur_model, cur_spin_id_str) 
3327   
3328          # Determine bounds for lower and upper 
3329          lower = [dx_point_clustered_min[0], dx_point_clustered_min[1], dx_point_clustered_min[2]] 
3330          upper = [19.0, 2.4, 9.5] 
3331   
3332          # Define temporary folder. 
3333          result_dir = self.tmpdir 
3334   
3335          # For testing. 
3336          #result_dir = None 
3337          #self.interpreter.relax_disp.cluster(cluster_id='free spins', spin_id=cur_spin_id) 
3338   
3339          # Then do the map. 
3340          self.interpreter.dx.map(params=dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=dx_inc, lower=lower, upper=upper, axis_incs=10, file_prefix=file_name_map, dir=result_dir, point=dx_point_clustered_min, point_file=file_name_point, create_par_file=True) 
3341   
3342          # Print where to locate values. 
3343          nr_chi2_val = (dx_inc + 1)**3 
3344          print("Nr of chi2 calculations are=%i"%nr_chi2_val) 
3345          print("Global chi2=%3.3f, Calc_chi=%3.3f" % (pre_chi2, calc_chi2) ) 
3346   
3347          ## Check for file creation 
3348          # Set filepaths. 
3349          map_name = get_file_path(file_name=file_name_map, dir=result_dir) 
3350          map_cfg = get_file_path(file_name=file_name_map+".cfg", dir=result_dir) 
3351          map_net = get_file_path(file_name=file_name_map+".net", dir=result_dir) 
3352          map_general = get_file_path(file_name=file_name_map+".general", dir=result_dir) 
3353          map_par = get_file_path(file_name=file_name_map+".par", dir=result_dir) 
3354   
3355          point_general = get_file_path(file_name=file_name_point+".general", dir=result_dir) 
3356          point_point = get_file_path(file_name=file_name_point, dir=result_dir) 
3357   
3358          # Test the files exists. 
3359          self.assert_(access(map_cfg, F_OK)) 
3360          self.assert_(access(map_net, F_OK)) 
3361          self.assert_(access(map_general, F_OK)) 
3362          self.assert_(access(map_par, F_OK)) 
3363          self.assert_(access(point_general, F_OK)) 
3364          self.assert_(access(point_point, F_OK)) 
3365   
3366          print("\nParams for dx map is") 
3367          print(dx_params) 
3368          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3369          print(dx_point_clustered_min, "\n") 
3370   
3371          # Open the parameter chi2 file, and assert the chi2 value in the sorted parameter file is not lower that than the global minimisation. 
3372          get_data = extract_data(file=map_par) 
3373   
3374          # Extract line 1, column 9. 
3375          test = float(get_data[1][9]) 
3376   
3377          # Print data if map contain a lower value than the global minimised value. 
3378          if test < pre_chi2: 
3379              print("\nInitial clustered minimised chi2 value is=%3.3f, whereby the minimum map value is=%3.3f\n" % (pre_chi2, test)) 
3380              for line in get_data: 
3381                  print(line) 
3382   
3383          # Assert that the initial global chi2 is lower than the map value. 
3384   
3385          # The following test was taken out, since this a particular interesting case. 
3386          # There exist a double minimum, where relax has not found the global minimum. 
3387          # This is due to not grid searching for R2A, but using the minimum  
3388          #self.assert_(pre_chi2 < test) 
3389   
3390   
3391 -    def test_estimate_r2eff_err(self): 
3392          """Test the user function for estimating R2eff errors from exponential curve fitting. 
3393   
3394          This follows Task 7822. 
3395          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3396   
3397          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3398          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3399          """ 
3400   
3401          # Cluster residues 
3402          cluster_ids = [ 
3403          ":13@N", 
3404          ":15@N", 
3405          ":16@N", 
3406          ":25@N", 
3407          ":26@N", 
3408          ":28@N", 
3409          ":39@N", 
3410          ":40@N", 
3411          ":41@N", 
3412          ":43@N", 
3413          ":44@N", 
3414          ":45@N", 
3415          ":49@N", 
3416          ":52@N", 
3417          ":53@N"] 
3418   
3419          # Load the data. 
3420          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
3421   
3422          # The dispersion models. 
3423          MODELS = [MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
3424   
3425          # The grid search size (the number of increments per dimension). 
3426          GRID_INC = None 
3427   
3428          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
3429          MC_NUM = 3 
3430   
3431          # Model selection technique. 
3432          MODSEL = 'AIC' 
3433   
3434          # Execute the auto-analysis (fast). 
3435          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
3436          OPT_FUNC_TOL = 1e-25 
3437          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
3438          OPT_MAX_ITERATIONS = 10000000 
3439          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
3440   
3441          result_dir_name = ds.tmpdir 
3442   
3443          # Make all spins free 
3444          for curspin in cluster_ids: 
3445              self.interpreter.relax_disp.cluster('free spins', curspin) 
3446              # Shut them down 
3447              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
3448   
3449          # Select only a subset of spins for global fitting 
3450          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
3451          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
3452   
3453          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
3454          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
3455   
3456          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
3457          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
3458   
3459          # Set the model. 
3460          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
3461   
3462          # Check if intensity errors have already been calculated. 
3463          check_intensity_errors() 
3464   
3465          # Do a grid search. 
3466          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=11, constraints=True, verbosity=1) 
3467   
3468          # Minimise. 
3469          self.interpreter.minimise.execute(min_algor='Newton', constraints=False, verbosity=1) 
3470   
3471          # Estimate R2eff errors. 
3472          self.interpreter.relax_disp.r2eff_err_estimate() 
3473   
3474          r1_fit = True 
3475   
3476          # Run the analysis. 
3477          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, r1_fit=r1_fit) 
3478   
3479          # Verify the data. 
3480          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='direct') 
3481   
3482   
3483 -    def test_estimate_r2eff_err_auto(self): 
3484          """Test the user function for estimating R2eff errors from exponential curve fitting, via the auto_analyses menu. 
3485   
3486          This follows Task 7822. 
3487          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3488   
3489          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3490          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3491          """ 
3492   
3493          # Cluster residues 
3494          cluster_ids = [ 
3495          ":13@N", 
3496          ":15@N", 
3497          ":16@N", 
3498          ":25@N", 
3499          ":26@N", 
3500          ":28@N", 
3501          ":39@N", 
3502          ":40@N", 
3503          ":41@N", 
3504          ":43@N", 
3505          ":44@N", 
3506          ":45@N", 
3507          ":49@N", 
3508          ":52@N", 
3509          ":53@N"] 
3510   
3511          # Load the data. 
3512          #self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
3513          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep 
3514   
3515          # Set pipe name, bundle and type. 
3516          pipe_name = 'base pipe' 
3517          pipe_bundle = 'relax_disp' 
3518          pipe_type = 'relax_disp' 
3519   
3520          # Create the data pipe. 
3521          self.interpreter.pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type=pipe_type) 
3522   
3523          file = data_path + '1_setup_r1rho_GUI.py' 
3524          self.interpreter.script(file=file, dir=None) 
3525   
3526          # The dispersion models. 
3527          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
3528   
3529          # The grid search size (the number of increments per dimension). 
3530          GRID_INC = None 
3531   
3532          # The number of Monte Carlo simulations to be used for error analysis for exponential curve fitting of R2eff. 
3533          # When set to minus 1, estimation of the errors will be extracted from the covariance matrix. 
3534          # This is HIGHLY likely to be wrong, but can be used in an initial test fase. 
3535          EXP_MC_NUM = -1 
3536   
3537          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
3538          MC_NUM = 3 
3539   
3540          # Model selection technique. 
3541          MODSEL = 'AIC' 
3542   
3543          # Execute the auto-analysis (fast). 
3544          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
3545          OPT_FUNC_TOL = 1e-25 
3546          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
3547          OPT_MAX_ITERATIONS = 10000000 
3548          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
3549   
3550          # Make all spins free 
3551          #for curspin in cluster_ids: 
3552          #    self.interpreter.relax_disp.cluster('free spins', curspin) 
3553          #    # Shut them down 
3554          #    self.interpreter.deselect.spin(spin_id=curspin, boolean='OR', change_all=False) 
3555   
3556          # Make all spins free 
3557          self.interpreter.deselect.spin(spin_id=':1-100', change_all=False) 
3558   
3559          # Select only a subset of spins for global fitting 
3560          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
3561          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
3562   
3563          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
3564          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
3565   
3566          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
3567          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
3568   
3569          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3570              print(spin_id) 
3571   
3572          result_dir_name = self.tmpdir 
3573          r1_fit = True 
3574   
3575          # Run the analysis. 
3576          relax_disp.Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, exp_mc_sim_num=EXP_MC_NUM, modsel=MODSEL, r1_fit=r1_fit) 
3577   
3578          # Verify the data. 
3579          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='direct') 
3580   
3581   
3582 -    def test_estimate_r2eff_err_methods(self): 
3583          """Test the user function for estimating R2eff and associated errors for exponential curve fitting with different methods. 
3584          This is compared with a run where erros are estimated by 2000 Monte Carlo simulations. 
3585   
3586          This follows Task 7822. 
3587          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3588   
3589          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3590          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3591   
3592          NOTE: The difference in the methods was due to a bug in relax! 
3593          U{bug #22554<https://gna.org/bugs/index.php?22554>}. The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected. 
3594   
3595          This dataset is old, and includes 2000 Monte-Carlo simulations, which is performed wrong. 
3596          """ 
3597   
3598          # Define data path. 
3599          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000"  +sep+ "R2eff" 
3600   
3601          # Create pipe. 
3602          self.interpreter.pipe.create('MC_2000', 'relax_disp') 
3603   
3604          # Read results for 2000 MC simulations. 
3605          self.interpreter.results.read(prev_data_path + sep + 'results') 
3606   
3607          # Start dic. 
3608          my_dic = {} 
3609          param_key_list = [] 
3610   
3611          # Do boot strapping ? 
3612          do_boot = True 
3613          if do_boot: 
3614              min_algor = 'Newton' 
3615              min_options = () 
3616              sim_boot = 200 
3617              scaling_list = [1.0, 1.0] 
3618   
3619          # First check sim values. 
3620          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3621              # Add key to dic. 
3622              my_dic[spin_id] = {} 
3623   
3624              # Loop over sim. 
3625              for i, r2eff_sim in enumerate(cur_spin.r2eff_sim): 
3626                  # Loop over all exp type. 
3627                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3628                      # Generate the param_key. 
3629                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3630                      r2eff_sim_point = r2eff_sim[param_key] 
3631                      i0_sim_point = cur_spin.r2eff_sim[i][param_key] 
3632   
3633                      # Assert point are higher than 0.0. 
3634                      #point_info = "r2eff=%3.2f i0=%3.2f, at %3.1f MHz, for offset=%3.3f ppm and dispersion point %-5.1f, at sim index %i." % (r2eff_sim_point, i0_sim_point, frq/1E6, offset, point, i) 
3635                      #print(point_info) 
3636                      self.assert_(r2eff_sim_point > 0.0) 
3637                      self.assert_(i0_sim_point > 0.0) 
3638   
3639          # Get the data. 
3640          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3641              # Generate spin string. 
3642              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
3643   
3644              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3645                  # Generate the param_key. 
3646                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3647   
3648                  # Loop over all sim, and collect data. 
3649                  r2eff_sim_l = [] 
3650                  i0_sim_l = [] 
3651                  for i, r2eff_sim in enumerate(cur_spin.r2eff_sim): 
3652                      i0_sim = cur_spin.i0_sim[i] 
3653   
3654                      r2eff_sim_i = r2eff_sim[param_key] 
3655                      r2eff_sim_l.append(r2eff_sim_i) 
3656                      i0_sim_i = i0_sim[param_key] 
3657                      i0_sim_l.append(i0_sim_i) 
3658   
3659                  # Take the standard deviation of all values. 
3660                  r2eff_sim_err = std(asarray(r2eff_sim_l), ddof=1) 
3661                  i0_sim_err = std(asarray(i0_sim_l), ddof=1) 
3662   
3663                  # Append key. 
3664                  param_key_list.append(param_key) 
3665   
3666                  # Add key to dic. 
3667                  my_dic[spin_id][param_key] = {} 
3668   
3669                  # Get the value. 
3670                  r2eff = getattr(cur_spin, 'r2eff')[param_key] 
3671                  r2eff_err = getattr(cur_spin, 'r2eff_err')[param_key] 
3672                  i0 = getattr(cur_spin, 'i0')[param_key] 
3673                  i0_err = getattr(cur_spin, 'i0_err')[param_key] 
3674   
3675                  # Save to dic. 
3676                  my_dic[spin_id][param_key]['r2eff'] = r2eff 
3677                  my_dic[spin_id][param_key]['r2eff_err'] = r2eff_err 
3678                  my_dic[spin_id][param_key]['i0'] = i0 
3679                  my_dic[spin_id][param_key]['i0_err'] = i0_err 
3680                  my_dic[spin_id][param_key]['r2eff_err_sim'] = r2eff_sim_err 
3681                  my_dic[spin_id][param_key]['i0_err_sim'] = i0_sim_err 
3682   
3683                  # Assert values are equal 
3684                  self.assertAlmostEqual(r2eff_sim_err, r2eff_err) 
3685                  self.assertAlmostEqual(i0_sim_err, i0_err) 
3686   
3687                  if do_boot: 
3688                      values = [] 
3689                      errors = [] 
3690                      times = [] 
3691                      for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
3692                          values.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)) 
3693                          errors.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)) 
3694                          times.append(time) 
3695   
3696                      # Convert to numpy array. 
3697                      values = asarray(values) 
3698                      errors = asarray(errors) 
3699                      times = asarray(times) 
3700   
3701                      R_m_sim_l = [] 
3702                      I0_m_sim_l = [] 
3703                      for j in range(sim_boot): 
3704                          if j in range(0, 100000, 100): 
3705                              print("Simulation %i"%j) 
3706                          # Start minimisation. 
3707   
3708                          # Produce errors 
3709                          I_err = [] 
3710                          for j, error in enumerate(errors): 
3711                              I_error = gauss(values[j], error) 
3712                              I_err.append(I_error) 
3713                          # Convert to numpy array. 
3714                          I_err = asarray(I_err) 
3715   
3716                          x0 = [r2eff, i0] 
3717                          model = Relax_fit_opt(model='exp', num_params=len(x0), values=I_err, errors=errors, relax_times=times, scaling_matrix=scaling_list) 
3718   
3719                          params_minfx_sim_j, chi2_minfx_sim_j, iter_count, f_count, g_count, h_count, warning = generic_minimise(func=model.func, dfunc=model.dfunc, d2func=model.d2func, args=(), x0=x0, min_algor=min_algor, min_options=min_options, full_output=True, print_flag=0) 
3720                          R_m_sim_j, I0_m_sim_j = params_minfx_sim_j 
3721                          R_m_sim_l.append(R_m_sim_j) 
3722                          I0_m_sim_l.append(I0_m_sim_j) 
3723   
3724                      # Get stats on distribution. 
3725                      sigma_R_sim = std(asarray(R_m_sim_l), ddof=1) 
3726                      sigma_I0_sim = std(asarray(I0_m_sim_l), ddof=1) 
3727                      my_dic[spin_id][param_key]['r2eff_err_boot'] = sigma_R_sim 
3728                      my_dic[spin_id][param_key]['i0_err_boot'] = sigma_I0_sim 
3729   
3730   
3731          # A new data pipe. 
3732          self.interpreter.pipe.copy(pipe_from='MC_2000', pipe_to='r2eff_est') 
3733          self.interpreter.pipe.switch(pipe_name='r2eff_est') 
3734   
3735          # Delete old errors. 
3736          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3737              delattr(cur_spin, 'r2eff_err') 
3738              delattr(cur_spin, 'i0_err') 
3739   
3740          # Set the model. 
3741          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
3742   
3743          # Estimate R2eff and errors. 
3744          self.interpreter.relax_disp.r2eff_err_estimate(verbosity=0) 
3745   
3746          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3747              # Generate spin string. 
3748              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
3749   
3750              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3751                  # Generate the param_key. 
3752                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3753   
3754                  # Get the value. 
3755                  r2eff_est = getattr(cur_spin, 'r2eff')[param_key] 
3756                  r2eff_err_est = getattr(cur_spin, 'r2eff_err')[param_key] 
3757                  i0_est = getattr(cur_spin, 'i0')[param_key] 
3758                  i0_err_est = getattr(cur_spin, 'i0_err')[param_key] 
3759   
3760                  # Get from dic. 
3761                  r2eff = my_dic[spin_id][param_key]['r2eff'] 
3762                  r2eff_err = my_dic[spin_id][param_key]['r2eff_err'] 
3763                  i0 = my_dic[spin_id][param_key]['i0'] 
3764                  i0_err = my_dic[spin_id][param_key]['i0_err'] 
3765                  r2eff_sim_err = my_dic[spin_id][param_key]['r2eff_err_sim'] 
3766                  i0_sim_err = my_dic[spin_id][param_key]['i0_err_sim'] 
3767   
3768                  if do_boot: 
3769                      r2eff_boot_err = my_dic[spin_id][param_key]['r2eff_err_boot'] 
3770                      i0_boot_err = my_dic[spin_id][param_key]['i0_err_boot'] 
3771                  else: 
3772                      r2eff_boot_err = 0.0 
3773                      i0_boot_err = 0.0 
3774   
3775                  print("%s at %3.1f MHz, for offset=%3.3f ppm and dispersion point %-5.1f." % (exp_type, frq/1E6, offset, point) ) 
3776                  print("r2eff=%3.3f/%3.3f r2eff_err=%3.4f/%3.4f/%3.4f/%3.4f" % (r2eff, r2eff_est, r2eff_err, r2eff_err_est, r2eff_sim_err, r2eff_boot_err) ), 
3777                  print("i0=%3.3f/%3.3f i0_err=%3.4f/%3.4f/%3.4f/%3.4f\n" % (i0, i0_est, i0_err, i0_err_est, i0_sim_err, i0_boot_err) ) 
3778   
3779   
3780          # Now do it manually. 
3781          estimate_r2eff(method='scipy.optimize.leastsq') 
3782   
3783          estimate_r2eff(method='minfx', min_algor='simplex', c_code=True, constraints=False, chi2_jacobian=False) 
3784          estimate_r2eff(method='minfx', min_algor='simplex', c_code=True, constraints=False, chi2_jacobian=True) 
3785   
3786          estimate_r2eff(method='minfx', min_algor='simplex', c_code=False, constraints=False, chi2_jacobian=False) 
3787          estimate_r2eff(method='minfx', min_algor='simplex', c_code=False, constraints=False, chi2_jacobian=True) 
3788   
3789          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=True, constraints=False, chi2_jacobian=False) 
3790          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=True, constraints=False, chi2_jacobian=True) 
3791   
3792          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=False, constraints=False, chi2_jacobian=False) 
3793          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=False, constraints=False, chi2_jacobian=True) 
3794   
3795          estimate_r2eff(method='minfx', min_algor='Newton', c_code=True, constraints=False, chi2_jacobian=False) 
3796          estimate_r2eff(method='minfx', min_algor='Newton', c_code=True, constraints=False, chi2_jacobian=True) 
3797   
3798   
3799   
3800 -    def test_exp_fit(self): 
3801          """Test the relaxation dispersion 'exp_fit' model curve fitting.""" 
3802   
3803          # Execute the script. 
3804          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'exp_fit.py') 
3805   
3806          # The original exponential curve parameters. 
3807          res_data = [ 
3808              [15., 10., 20000., 25000.], 
3809              [12., 11., 50000., 51000.], 
3810              [17., 9., 100000., 96000.] 
3811          ] 
3812   
3813          # List of parameters which do not belong to the model. 
3814          blacklist = ['cpmg_frqs', 'r2', 'rex', 'kex', 'r2a', 'k_AB', 'dw'] 
3815   
3816          # Checks for each residue. 
3817          for i in range(len(res_data)): 
3818              # Printout. 
3819              print("\nResidue number %s." % (i+1)) 
3820   
3821              # Check the fitted parameters. 
3822              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].r2eff['r1rho_1200.00000000_0.000_1000.000'], res_data[i][0], places=2) 
3823              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].r2eff['r1rho_1200.00000000_0.000_2000.000'], res_data[i][1], places=2) 
3824              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].i0['r1rho_1200.00000000_0.000_1000.000']/10000, res_data[i][2]/10000, places=3) 
3825              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].i0['r1rho_1200.00000000_0.000_2000.000']/10000, res_data[i][3]/10000, places=3) 
3826   
3827              # Check the simulation errors. 
3828              self.assert_(cdp.mol[0].res[i].spin[0].r2eff_err['r1rho_1200.00000000_0.000_1000.000'] < 5.0) 
3829              self.assert_(cdp.mol[0].res[i].spin[0].r2eff_err['r1rho_1200.00000000_0.000_2000.000'] < 5.0) 
3830              self.assert_(cdp.mol[0].res[i].spin[0].i0_err['r1rho_1200.00000000_0.000_1000.000']/10000 < 5.0) 
3831              self.assert_(cdp.mol[0].res[i].spin[0].i0_err['r1rho_1200.00000000_0.000_2000.000']/10000 < 5.0) 
3832   
3833              # Check that certain parameters are not present. 
3834              for param in blacklist: 
3835                  print("\tChecking for the absence of the '%s' parameter." % param) 
3836                  self.assert_(not hasattr(cdp.mol[0].res[i].spin[0], param)) 
3837   
3838          # Check the clustering information. 
3839          self.assert_(hasattr(cdp, 'clustering')) 
3840          keys = ['free spins', 'cluster'] 
3841          for key in keys: 
3842              self.assert_(key in cdp.clustering) 
3843          self.assert_('test' not in cdp.clustering) 
3844          self.assertEqual(cdp.clustering['free spins'], [':2@N']) 
3845          self.assertEqual(cdp.clustering['cluster'], [':1@N', ':3@N']) 
3846   
3847   
3848 -    def test_finite_value(self): 
3849          """Test return from C code, when parameters are wrong.  This can happen, if minfx takes a wrong step.""" 
3850   
3851          times = array([ 0.7,  1.,  0.8,  0.4,  0.9]) 
3852          I = array([ 476.76174875,  372.43328777,  454.20339981,  656.87936253,  419.16726341]) 
3853          errors = array([  9.48032653,  11.34093541,   9.35149017,  10.84867928,  12.17590736]) 
3854   
3855          scaling_list = [1.0, 1.0] 
3856          model = Relax_fit_opt(model='exp', num_params=2, values=I, errors=errors, relax_times=times, scaling_matrix=scaling_list) 
3857   
3858          R = - 500. 
3859          I0 = 1000. 
3860          params = [R, I0] 
3861   
3862          chi2 = model.func(params) 
3863   
3864          print("The chi2 value returned from C-code for R=%3.2f and I0=%3.2f, then chi2=%3.2f"%(R, I0, chi2)) 
3865          self.assertNotEqual(chi2, inf) 
3866   
3867   
3868 -    def test_hansen_catia_input(self): 
3869          """Conversion of Dr. Flemming Hansen's CPMG R2eff values into input files for CATIA. 
3870   
3871          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3872          """ 
3873   
3874          # Load the R2eff results file. 
3875          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'r2eff_pipe' 
3876          self.interpreter.results.read(file_name) 
3877          self.interpreter.deselect.spin(':4') 
3878   
3879          # The spin isotopes. 
3880          self.interpreter.spin.isotope("15N") 
3881   
3882          # Generate the input files. 
3883          self.interpreter.relax_disp.catia_input(dir=ds.tmpdir, force=True) 
3884   
3885          # Check the r2eff set files. 
3886          print("\nChecking the R2eff input set files.") 
3887          files = ['data_set_500.inp', 'data_set_500.inp'] 
3888          for file in files: 
3889              self.assert_(access(ds.tmpdir+sep+file, F_OK)) 
3890          data_set_500 = [ 
3891              "ID=500\n", 
3892              "Sfrq = 500\n", 
3893              "Temperature = 0.0\n", 
3894              "Nucleus = N15\n", 
3895              "Couplednucleus = H1\n", 
3896              "Time_equil = 0.0\n", 
3897              "Pwx_cp = 0.0\n", 
3898              "Taub = 0.0\n", 
3899              "Time_T2 = 0.03\n", 
3900              "Xcar = 0.0\n", 
3901              "Seqfil = CW_CPMG\n", 
3902              "Minerror = (2.%;0.5/s)\n", 
3903              "Basis = (Iph_7)\n", 
3904              "Format = (0;1;2)\n", 
3905              "DataDirectory = /tmp/tmpNjOGNG/input_r2eff\n", 
3906              "Data = (\n", 
3907              " [70N;spin_70_N_500.cpmg];\n", 
3908              " [71N;spin_71_N_500.cpmg];\n", 
3909              ")\n", 
3910          ] 
3911          file = open(ds.tmpdir+sep+files[0]) 
3912          lines = file.readlines() 
3913          file.close() 
3914          for i in range(len(data_set_500)): 
3915              # Skip the data directory, as this is a random file name. 
3916              if i == 14: 
3917                  continue 
3918   
3919              self.assertEqual(data_set_500[i], lines[i]) 
3920   
3921          # Check the r2eff files. 
3922          print("\nChecking the R2eff input files.") 
3923          files = ['spin_70_N_500.cpmg', 'spin_70_N_800.cpmg', 'spin_71_N_500.cpmg', 'spin_71_N_800.cpmg'] 
3924          for file in files: 
3925              self.assert_(access(ds.tmpdir+sep+'input_r2eff'+sep+file, F_OK)) 
3926          spin_70_N_500 = [ 
3927              "#        nu_cpmg(Hz)              R2(1/s)              Esd(R2)\n", 
3928              "  66.666600000000003   16.045540885533605    0.310924686180635\n", 
3929              " 133.333300000000008   14.877924861181727    0.303217270671013\n", 
3930              " 200.000000000000000   14.357820247260586    0.299894424543361\n", 
3931              " 266.666600000000017   12.664494620416516    0.289532060485796\n", 
3932              " 333.333300000000008   12.363204802467891    0.287759631749322\n", 
3933              " 400.000000000000000   11.092532381134513    0.280514035409862\n", 
3934              " 466.666600000000017   10.566090057649893    0.277618625949722\n", 
3935              " 533.333300000000008    9.805806894657803    0.273544382200754\n", 
3936              " 600.000000000000000    9.564300692201730    0.272276309984954\n", 
3937              " 666.666600000000017    9.015633750407980    0.269441511838159\n", 
3938              " 733.333300000000008    8.607764958055581    0.267375134391053\n", 
3939              " 800.000000000000000    8.279997179221338    0.265739551961997\n", 
3940              " 866.666600000000017    8.474535940963516    0.266707642726566\n", 
3941              " 933.333300000000008    8.158972897365194    0.265141210539941\n", 
3942              "1000.000000000000000    7.988630509501972    0.264304105548559\n", 
3943          ] 
3944          file = open(ds.tmpdir+sep+'input_r2eff'+sep+files[0]) 
3945          lines = file.readlines() 
3946          file.close() 
3947          for i in range(len(lines)): 
3948              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
3949          for i in range(len(spin_70_N_500)): 
3950              self.assertEqual(spin_70_N_500[i], lines[i]) 
3951   
3952          # Check the main file. 
3953          print("\nChecking the main CATIA execution file.") 
3954          main_file = [ 
3955              "ReadDataset(data_set_500.inp)\n", 
3956              "ReadDataset(data_set_800.inp)\n", 
3957              "ReadParam_Global(ParamGlobal.inp)\n", 
3958              "ReadParam_Local(ParamSet1.inp)\n", 
3959              "\n", 
3960              "FreeLocalParam(all;Omega;false)\n", 
3961              "FreeLocalParam(all;R1iph_500;false)\n", 
3962              "FreeLocalParam(all;R1iph_800;false)\n", 
3963              "\n", 
3964              "Minimize(print=y;tol=1e-25;maxiter=10000000)\n", 
3965              "\n", 
3966              "PrintParam(output/GlobalParam.fit;global)\n", 
3967              "PrintParam(output/DeltaOmega.fit;DeltaO)\n", 
3968              "PrintData(output/)\n", 
3969              "\n", 
3970              "ChiSq(all;all)\n", 
3971              "exit(0)\n" 
3972          ] 
3973          file = open("%s%sFit.catia" % (ds.tmpdir, sep)) 
3974          lines = file.readlines() 
3975          file.close() 
3976          for i in range(len(main_file)): 
3977              self.assertEqual(main_file[i], lines[i]) 
3978   
3979   
3980 -    def test_hansen_cpmg_data_auto_analysis(self): 
3981          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data. 
3982   
3983          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3984          """ 
3985   
3986          # Set the model. 
3987          ds.models = [ 
3988              MODEL_NOREX, 
3989              MODEL_LM63, 
3990              MODEL_CR72, 
3991              MODEL_IT99 
3992          ] 
3993   
3994          # Execute the script. 
3995          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data.py') 
3996          self.interpreter.state.save('analysis_heights', dir=ds.tmpdir, force=True) 
3997   
3998          # The R20 keys. 
3999          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4000          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4001   
4002          # The 'No Rex' model checks. 
4003          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4004          spin70 = return_spin(":70") 
4005          spin71 = return_spin(":71") 
4006          print("\n\nOptimised parameters:\n") 
4007          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4008          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4009          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4010          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4011          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
4012          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
4013          self.assertAlmostEqual(spin70.chi2, 8973.84810025761, 3) 
4014          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
4015          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
4016          self.assertAlmostEqual(spin71.chi2, 3908.00127830003, 3) 
4017   
4018          # The 'LM63' model checks. 
4019          self.interpreter.pipe.switch(pipe_name='LM63 - relax_disp') 
4020          spin70 = return_spin(":70") 
4021          spin71 = return_spin(":71") 
4022          print("\n\nOptimised parameters:\n") 
4023          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4024          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4025          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4026          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
4027          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4028          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4029          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74326615264889, 2) 
4030          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57331164382438, 2) 
4031          self.assertAlmostEqual(spin70.phi_ex, 0.312767653822936, 3) 
4032          self.assertAlmostEqual(spin70.kex/10000, 4723.44390412119/10000, 3) 
4033          self.assertAlmostEqual(spin70.chi2, 363.534049046805, 3) 
4034          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00778024769786, 3) 
4035          self.assertAlmostEqual(spin71.r2[r20_key2], 6.83343630016037, 3) 
4036          self.assertAlmostEqual(spin71.phi_ex, 0.0553791362097596, 3) 
4037          self.assertAlmostEqual(spin71.kex/10000, 2781.67925957068/10000, 3) 
4038          self.assertAlmostEqual(spin71.chi2, 17.0776426190574, 3) 
4039   
4040          # The 'CR72' model checks. 
4041          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4042          spin70 = return_spin(":70") 
4043          spin71 = return_spin(":71") 
4044          print("\n\nOptimised parameters:\n") 
4045          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4046          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4047          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4048          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4049          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4050          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4051          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4052          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
4053          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
4054          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
4055          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
4056          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
4057          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
4058          self.assertAlmostEqual(spin71.r2[r20_key1], 5.003171547206, 3) 
4059          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797727492, 3) 
4060          self.assertAlmostEqual(spin71.pA, 0.985922406455826, 3) 
4061          self.assertAlmostEqual(spin71.dw, 2.00500965892672, 2) 
4062          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579617/10000, 3) 
4063          self.assertAlmostEqual(spin71.chi2, 15.6595374286822, 3) 
4064   
4065   
4066 -    def test_hansen_cpmg_data_auto_analysis_numeric(self): 
4067          """Test of the numeric model only dispersion auto-analysis using Dr. Flemming Hansen's CPMG data. 
4068   
4069          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4070          """ 
4071   
4072          # Set the model and numeric flag. 
4073          ds.models = [ 
4074              MODEL_NOREX, 
4075              MODEL_CR72, 
4076              MODEL_NS_CPMG_2SITE_EXPANDED 
4077          ] 
4078          ds.numeric_only = True 
4079   
4080          # Execute the script. 
4081          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data.py') 
4082   
4083          # The R20 keys. 
4084          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4085          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4086   
4087          # The 'No Rex' model checks. 
4088          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4089          spin70 = return_spin(":70") 
4090          spin71 = return_spin(":71") 
4091          print("\n\nOptimised parameters:\n") 
4092          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4093          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4094          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4095          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4096          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
4097          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
4098          self.assertAlmostEqual(spin70.chi2/10000, 8973.84810025761/10000, 3) 
4099          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
4100          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
4101          self.assertAlmostEqual(spin71.chi2/10000, 3908.00127830003/10000, 3) 
4102   
4103          # The 'CR72' model checks. 
4104          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4105          spin70 = return_spin(":70") 
4106          spin71 = return_spin(":71") 
4107          print("\n\nOptimised parameters:\n") 
4108          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4109          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4110          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4111          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4112          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4113          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4114          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4115          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
4116          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
4117          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
4118          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
4119          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
4120          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
4121          self.assertAlmostEqual(spin71.r2[r20_key1], 5.003171547206, 3) 
4122          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797727492, 3) 
4123          self.assertAlmostEqual(spin71.pA, 0.985922406455826, 3) 
4124          self.assertAlmostEqual(spin71.dw, 2.00500965892672, 2) 
4125          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579617/10000, 3) 
4126          self.assertAlmostEqual(spin71.chi2, 15.6595374286822, 3) 
4127   
4128          # The 'NS CPMG 2-site expanded' model checks. 
4129          self.interpreter.pipe.switch(pipe_name='NS CPMG 2-site expanded - relax_disp') 
4130          spin70 = return_spin(":70") 
4131          spin71 = return_spin(":71") 
4132          print("\n\nOptimised parameters:\n") 
4133          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4134          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4135          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4136          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4137          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4138          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4139          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4140          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95815351460902, 3) 
4141          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39649535771294, 3) 
4142          self.assertAlmostEqual(spin70.pA, 0.989701014493195, 3) 
4143          self.assertAlmostEqual(spin70.dw, 5.67314464776128, 3) 
4144          self.assertAlmostEqual(spin70.kex/10000, 1713.65380495429/10000, 3) 
4145          self.assertAlmostEqual(spin70.chi2, 52.5106880917473, 3) 
4146          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99889337382435, 3) 
4147          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89822887466673, 3) 
4148          self.assertAlmostEqual(spin71.pA, 0.986709050819695, 3) 
4149          self.assertAlmostEqual(spin71.dw, 2.09238266766502, 2) 
4150          self.assertAlmostEqual(spin71.kex/10000, 2438.27019901422/10000, 3) 
4151          self.assertAlmostEqual(spin71.chi2, 15.1644906963987, 3) 
4152   
4153          # The final data pipe checks. 
4154          self.interpreter.pipe.switch(pipe_name='final - relax_disp') 
4155          spin70 = return_spin(":70") 
4156          spin71 = return_spin(":71") 
4157          self.assertEqual(spin70.model, 'NS CPMG 2-site expanded') 
4158          self.assertEqual(spin71.model, 'NS CPMG 2-site expanded') 
4159   
4160   
4161 -    def test_hansen_cpmg_data_auto_analysis_r2eff(self): 
4162          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data (using the R2eff data directly instead of peak intensities). 
4163   
4164          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4165          """ 
4166   
4167          # Set the model. 
4168          ds.models = [ 
4169              MODEL_NOREX, 
4170              MODEL_LM63, 
4171              MODEL_CR72, 
4172              MODEL_IT99 
4173          ] 
4174   
4175          # Execute the script. 
4176          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_r2eff_data.py') 
4177          self.interpreter.state.save('analysis_r2eff', dir=ds.tmpdir, force=True) 
4178   
4179          # The R20 keys. 
4180          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4181          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4182   
4183          # The 'No Rex' model checks. 
4184          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4185          spin70 = return_spin(":70") 
4186          spin71 = return_spin(":71") 
4187          print("\n\nOptimised parameters:\n") 
4188          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4189          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4190          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4191          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4192          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
4193          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
4194          self.assertAlmostEqual(spin70.chi2, 8973.84810025761, 3) 
4195          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
4196          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
4197          self.assertAlmostEqual(spin71.chi2, 3908.00127830003, 3) 
4198   
4199          # The 'LM63' model checks. 
4200          self.interpreter.pipe.switch(pipe_name='LM63 - relax_disp') 
4201          spin70 = return_spin(":70") 
4202          spin71 = return_spin(":71") 
4203          print("\n\nOptimised parameters:\n") 
4204          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4205          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4206          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4207          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
4208          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4209          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4210          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74326615264889, 2) 
4211          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57331164382438, 2) 
4212          self.assertAlmostEqual(spin70.phi_ex, 0.312767653822936, 3) 
4213          self.assertAlmostEqual(spin70.kex/10000, 4723.44390412119/10000, 3) 
4214          self.assertAlmostEqual(spin70.chi2, 363.534049046805, 3) 
4215          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00778024769786, 3) 
4216          self.assertAlmostEqual(spin71.r2[r20_key2], 6.83343630016037, 3) 
4217          self.assertAlmostEqual(spin71.phi_ex, 0.0553791362097596, 3) 
4218          self.assertAlmostEqual(spin71.kex/10000, 2781.67925957068/10000, 3) 
4219          self.assertAlmostEqual(spin71.chi2, 17.0776426190574, 3) 
4220   
4221          # The 'CR72' model checks. 
4222          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4223          spin70 = return_spin(":70") 
4224          spin71 = return_spin(":71") 
4225          print("\n\nOptimised parameters:\n") 
4226          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4227          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4228          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4229          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4230          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4231          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4232          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4233          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
4234          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
4235          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
4236          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
4237          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
4238          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
4239          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00317154730225, 3) 
4240          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797713541, 3) 
4241          self.assertAlmostEqual(spin71.pA, 0.985922406429147, 3) 
4242          self.assertAlmostEqual(spin71.dw, 2.00500965887772, 2) 
4243          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579804/10000, 3) 
4244          self.assertAlmostEqual(spin71.chi2, 15.6595374288635, 3) 
4245   
4246   
4247 -    def test_hansen_cpmg_data_missing_auto_analysis(self): 
4248          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data with parts missing. 
4249   
4250          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4251          """ 
4252   
4253          # Set the model. 
4254          ds.models = [ 
4255              MODEL_R2EFF, 
4256              MODEL_NOREX, 
4257              MODEL_CR72, 
4258              MODEL_NS_CPMG_2SITE_EXPANDED 
4259          ] 
4260   
4261          # Execute the script. 
4262          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data_missing.py') 
4263          self.interpreter.state.save('analysis_heights', dir=ds.tmpdir, force=True) 
4264   
4265          # The R20 keys. 
4266          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4267          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4268   
4269          # The 'No Rex' model checks. 
4270          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4271          spin4 = return_spin(":4") 
4272          spin70 = return_spin(":70") 
4273          spin71 = return_spin(":71") 
4274          print("\n\nOptimised parameters:\n") 
4275          print("%-20s %-20s %-20s %-20s" % ("Parameter", "Value (:4)", "Value (:70)", "Value (:71)")) 
4276          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin4.r2[r20_key1], spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4277          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin4.r2[r20_key2], spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4278          print("%-20s %20.15g %20.15g %20.15g\n" % ("chi2", spin4.chi2, spin70.chi2, spin71.chi2)) 
4279          self.assertAlmostEqual(spin4.r2[r20_key1], 1.60463084515171, 3) 
4280          self.assertAlmostEqual(spin4.r2[r20_key2], 1.63220784651911, 3) 
4281          self.assertAlmostEqual(spin4.chi2, 26.7356700694891, 3) 
4282          self.assertAlmostEqual(spin70.r2[r20_key1], 10.534285641325, 3) 
4283          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112794857068, 3) 
4284          self.assertAlmostEqual(spin70.chi2, 8973.84809774722, 3) 
4285          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83136858890037, 3) 
4286          self.assertAlmostEqual(spin71.chi2, 182.60081909193, 3) 
4287   
4288          # The 'CR72' model checks. 
4289          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4290          spin4 = return_spin(":4") 
4291          spin70 = return_spin(":70") 
4292          spin71 = return_spin(":71") 
4293          print("\n\nOptimised parameters:\n") 
4294          print("%-20s %-20s %-20s %-20s" % ("Parameter", "Value (:4)", "Value (:70)", "Value (:71)")) 
4295          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin4.r2[r20_key1], spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4296          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin4.r2[r20_key2], spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4297          print("%-20s %20.15g %20.15g %20.15g" % ("pA", spin4.pA, spin70.pA, spin71.pA)) 
4298          print("%-20s %20.15g %20.15g %20.15g" % ("dw", spin4.dw, spin70.dw, spin71.dw)) 
4299          print("%-20s %20.15g %20.15g %20.15g" % ("kex", spin4.kex, spin70.kex, spin71.kex)) 
4300          print("%-20s %20.15g %20.15g %20.15g\n" % ("chi2", spin4.chi2, spin70.chi2, spin71.chi2)) 
4301          self.assertAlmostEqual(spin4.r2[r20_key1], 1.60463650370664, 2) 
4302          self.assertAlmostEqual(spin4.r2[r20_key2], 1.63221675941434, 3) 
4303          #self.assertAlmostEqual(spin4.pA, 0.818979078699935, 3)    # As dw (and kex) is zero, this parameter is not stable. 
4304          self.assertAlmostEqual(spin4.dw, 0.0, 2) 
4305          self.assertAlmostEqual(spin4.kex/10000, 0.0, 3) 
4306          self.assertAlmostEqual(spin4.chi2/100, 26.7356711142038/100, 3) 
4307          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97268077496405, 3) 
4308          self.assertAlmostEqual(spin70.r2[r20_key2], 9.41028133407727, 3) 
4309          self.assertAlmostEqual(spin70.pA, 0.989856641885939, 3) 
4310          self.assertAlmostEqual(spin70.dw, 5.60889911049405, 3) 
4311          self.assertAlmostEqual(spin70.kex/10000, 1752.62025618632/10000, 3) 
4312          self.assertAlmostEqual(spin70.chi2, 53.8382196964083, 3) 
4313          self.assertAlmostEqual(spin71.r2[r20_key1], 4.98123328466942, 3) 
4314          self.assertAlmostEqual(spin71.pA, 0.996607425484157, 3) 
4315          self.assertAlmostEqual(spin71.dw, 4.34346257383825, 2) 
4316          self.assertAlmostEqual(spin71.kex/10000, 1936.73197158804/10000, 3) 
4317          self.assertAlmostEqual(spin71.chi2, 5.51703791653689, 3) 
4318   
4319   
4320 -    def test_hansen_cpmg_data_to_cr72(self): 
4321          """Optimisation of Dr. Flemming Hansen's CPMG data to the CR72 dispersion model. 
4322   
4323          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4324          """ 
4325   
4326          # Base data setup. 
4327          self.setup_hansen_cpmg_data(model='CR72') 
4328   
4329          # Alias the spins. 
4330          spin70 = return_spin(":70") 
4331          spin71 = return_spin(":71") 
4332   
4333          # The R20 keys. 
4334          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4335          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4336   
4337          # Set the initial parameter values. 
4338          spin70.r2 = {r20_key1: 7.0, r20_key2: 9.0} 
4339          spin70.pA = 0.9 
4340          spin70.dw = 6.0 
4341          spin70.kex = 1500.0 
4342          spin71.r2 = {r20_key1: 5, r20_key2: 9.0} 
4343          spin71.pA = 0.9 
4344          spin71.dw = 4.0 
4345          spin71.kex = 1900.0 
4346   
4347          # Low precision optimisation. 
4348          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4349   
4350          # Printout. 
4351          print("\n\nOptimised parameters:\n") 
4352          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4353          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4354          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4355          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4356          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4357          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4358          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4359   
4360          # Checks for residue :70. 
4361          self.assertAlmostEqual(spin70.r2[r20_key1], 6.9724581325007, 4) 
4362          self.assertAlmostEqual(spin70.r2[r20_key2], 9.40968331038162, 2) 
4363          self.assertAlmostEqual(spin70.pA, 0.989856656702431, 4) 
4364          self.assertAlmostEqual(spin70.dw, 5.60885879594746, 3) 
4365          self.assertAlmostEqual(spin70.kex/1000, 1752.91052702273/1000, 3) 
4366          self.assertAlmostEqual(spin70.chi2, 53.8382133597495, 4) 
4367   
4368          # Checks for residue :71. 
4369          self.assertAlmostEqual(spin71.r2[r20_key1], 5.0030740940524, 4) 
4370          self.assertAlmostEqual(spin71.pA, 0.985941082507823, 4) 
4371          self.assertAlmostEqual(spin71.dw, 2.00640384113696, 4) 
4372          self.assertAlmostEqual(spin71.kex/1000, 2480.79614442041/1000, 4) 
4373          self.assertAlmostEqual(spin71.chi2, 15.6595388312451, 4) 
4374   
4375          # Test the conversion to k_AB from kex and pA. 
4376          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4377          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4378   
4379          # Test the conversion to k_BA from kex and pA. 
4380          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4381          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4382   
4383   
4384 -    def test_hansen_cpmg_data_to_cr72_full(self): 
4385          """Optimisation of Dr. Flemming Hansen's CPMG data to the CR72 full dispersion model. 
4386   
4387          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4388          """ 
4389   
4390          # Base data setup. 
4391          self.setup_hansen_cpmg_data(model='CR72 full') 
4392   
4393          # Alias the spins. 
4394          spin70 = return_spin(":70") 
4395          spin71 = return_spin(":71") 
4396   
4397          # The R20 keys. 
4398          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4399          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4400   
4401          # Set the initial parameter values. 
4402          spin70.r2a = {r20_key1: 7.0, r20_key2: 9.0} 
4403          spin70.r2b = {r20_key1: 7.0, r20_key2: 9.0} 
4404          spin70.pA = 0.9 
4405          spin70.dw = 6.0 
4406          spin70.kex = 1500.0 
4407          spin71.r2a = {r20_key1: 5.0, r20_key2: 9.0} 
4408          spin71.r2b = {r20_key1: 5.0, r20_key2: 9.0} 
4409          spin71.pA = 0.9 
4410          spin71.dw = 4.0 
4411          spin71.kex = 1900.0 
4412   
4413          # Low precision optimisation. 
4414          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4415   
4416          # Printout. 
4417          print("\n\nOptimised parameters:\n") 
4418          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4419          print("%-20s %20.15g %20.15g" % ("R2A (500 MHz)", spin70.r2a[r20_key1], spin71.r2a[r20_key1])) 
4420          print("%-20s %20.15g %20.15g" % ("R2B (500 MHz)", spin70.r2b[r20_key1], spin71.r2b[r20_key1])) 
4421          print("%-20s %20.15g %20.15g" % ("R2A (800 MHz)", spin70.r2a[r20_key2], spin71.r2a[r20_key2])) 
4422          print("%-20s %20.15g %20.15g" % ("R2B (800 MHz)", spin70.r2b[r20_key2], spin71.r2b[r20_key2])) 
4423          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4424          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4425          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4426          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4427   
4428          # Checks for residue :70. 
4429          self.assertAlmostEqual(spin70.r2a[r20_key1], 6.87485258365614, 4) 
4430          self.assertAlmostEqual(spin70.r2b[r20_key1], 1.26075839074614, 4) 
4431          self.assertAlmostEqual(spin70.r2a[r20_key2], 8.79580446260797, 4) 
4432          self.assertAlmostEqual(spin70.r2b[r20_key2], 51.188411562843, 4) 
4433          self.assertAlmostEqual(spin70.pA, 0.989384178573802, 4) 
4434          self.assertAlmostEqual(spin70.dw, 5.54738203723682, 4) 
4435          self.assertAlmostEqual(spin70.kex/1000, 1831.4566463179/1000, 4) 
4436          self.assertAlmostEqual(spin70.chi2, 50.450410782403, 4) 
4437   
4438          # Checks for residue :71. 
4439          self.assertAlmostEqual(spin71.r2a[r20_key1], 5.04185695754972, 4) 
4440          self.assertAlmostEqual(spin71.r2b[r20_key1], 1.62857899941921, 4) 
4441          self.assertAlmostEqual(spin71.pA, 0.988832866751676, 4) 
4442          self.assertAlmostEqual(spin71.dw, 2.24905251856265, 4) 
4443          self.assertAlmostEqual(spin71.kex/1000, 2397.64122642946/1000, 4) 
4444          self.assertAlmostEqual(spin71.chi2, 15.8586492923672, 4) 
4445   
4446          # Test the conversion to k_AB from kex and pA. 
4447          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4448          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4449   
4450          # Test the conversion to k_BA from kex and pA. 
4451          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4452          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4453   
4454   
4455 -    def test_hansen_cpmg_data_to_it99(self): 
4456          """Optimisation of Dr. Flemming Hansen's CPMG data to the IT99 dispersion model. 
4457   
4458          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4459          """ 
4460   
4461          # Base data setup. 
4462          self.setup_hansen_cpmg_data(model='IT99') 
4463   
4464          # Alias the spins. 
4465          spin70 = return_spin(":70") 
4466          spin71 = return_spin(":71") 
4467   
4468          # The R20 keys. 
4469          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4470          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4471   
4472          # Set the initial parameter values. 
4473          spin70.r2 = {r20_key1: 8.8, r20_key2: 16.6} 
4474          spin70.dw = 10.0 
4475          spin70.pA = 0.5 
4476          spin70.tex = 1000.09 
4477          spin71.r2 = {r20_key1: 1.0, r20_key2: 1.0} 
4478          spin71.dw = 10.0 
4479          spin71.pA = 0.95 
4480          spin71.tex = 0.1 
4481   
4482          # Low precision optimisation. 
4483          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-10, grad_tol=None, max_iter=10000, constraints=True, scaling=True, verbosity=1) 
4484   
4485          # Printout. 
4486          print("\n\nOptimised parameters:\n") 
4487          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4488          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4489          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4490          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4491          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4492          print("%-20s %20.15g %20.15g" % ("tex", spin70.tex, spin71.tex)) 
4493          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4494   
4495          # Checks for residue :70. 
4496          self.assertAlmostEqual(spin70.r2[r20_key1], 7.24471197811838, 4) 
4497          self.assertAlmostEqual(spin70.r2[r20_key2], 10.0571040704729, 4) 
4498          self.assertAlmostEqual(spin70.dw, 5.2116923222744, 4) 
4499          self.assertAlmostEqual(spin70.pA, 0.990253627907212, 4) 
4500          self.assertAlmostEqual(spin70.tex*1000, 0.000638394793480444*1000, 4) 
4501          self.assertAlmostEqual(spin70.chi2, 93.5135798618747, 4) 
4502   
4503          # Checks for residue :71. 
4504          self.assertAlmostEqual(spin71.r2[r20_key1], 5.05971235970214, 4) 
4505          self.assertAlmostEqual(spin71.r2[r20_key2], 6.96641194493447, 4) 
4506          self.assertAlmostEqual(spin71.dw, 0.435389946897141, 4) 
4507          self.assertAlmostEqual(spin71.pA, 0.500000000213519, 3) 
4508          self.assertAlmostEqual(spin71.tex*1000, 0.000372436400585538*1000, 4) 
4509          self.assertAlmostEqual(spin71.chi2, 23.7895798801404, 4) 
4510   
4511   
4512 -    def test_hansen_cpmg_data_to_lm63(self): 
4513          """Optimisation of Dr. Flemming Hansen's CPMG data to the LM63 dispersion model. 
4514   
4515          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4516          """ 
4517   
4518          # Base data setup. 
4519          self.setup_hansen_cpmg_data(model='LM63') 
4520   
4521          # Alias the spins. 
4522          spin70 = return_spin(":70") 
4523          spin71 = return_spin(":71") 
4524   
4525          # The R20 keys. 
4526          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4527          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4528   
4529          # Set the initial parameter values. 
4530          spin70.r2 = {r20_key1: 7.0, r20_key2: 7.0} 
4531          spin70.phi_ex = 0.3 
4532          spin70.kex = 5000.0 
4533          spin71.r2 = {r20_key1: 5.0, r20_key2: 9.0} 
4534          spin71.phi_ex = 0.1 
4535          spin71.kex = 2500.0 
4536   
4537          # Low precision optimisation. 
4538          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None, max_iter=10000000, constraints=True, scaling=True, verbosity=1) 
4539   
4540          # Printout. 
4541          print("\n\nOptimised parameters:\n") 
4542          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4543          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4544          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4545          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
4546          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4547          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4548   
4549          # Checks for residue :70. 
4550          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74362294539099) 
4551          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57406797067481, 6) 
4552          self.assertAlmostEqual(spin70.phi_ex, 0.312733013751449) 
4553          self.assertAlmostEqual(spin70.kex/1000, 4723.09897146338/1000, 6) 
4554          self.assertAlmostEqual(spin70.chi2, 363.534044873483) 
4555   
4556          # Checks for residue :71. 
4557          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00776657729728, 5) 
4558          self.assertAlmostEqual(spin71.phi_ex, 0.0553787825650613, 5) 
4559          self.assertAlmostEqual(spin71.kex/1000, 2781.72292994154/1000, 5) 
4560          self.assertAlmostEqual(spin71.chi2, 17.0776399916287, 5) 
4561   
4562   
4563 -    def test_hansen_cpmg_data_to_lm63_3site(self): 
4564          """Optimisation of Dr. Flemming Hansen's CPMG data to the LM63 dispersion model. 
4565   
4566          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4567          """ 
4568   
4569          # Base data setup. 
4570          self.setup_hansen_cpmg_data(model='LM63 3-site') 
4571   
4572          # Alias the spins. 
4573          spin70 = return_spin(":70") 
4574          spin71 = return_spin(":71") 
4575   
4576          # The R20 keys. 
4577          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4578          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4579   
4580          ## Set the initial parameter values. 
4581          spin70.r2 = {r20_key1: 7.570370921220954, r20_key2: 8.694446951909107} 
4582          spin70.phi_ex_B = 0.14872003058250227 
4583          spin70.phi_ex_C = 0.1319419923472704 
4584          spin70.kB = 4103.672910444741 
4585          spin70.kC = 7029.001690726248 
4586          spin71.r2 = {r20_key1: 5.1347793381636, r20_key2: 7.156573986051575} 
4587          spin71.phi_ex_B = 0.04013553485505605 
4588          spin71.phi_ex_C = 0.020050748406928887 
4589          spin71.kB = 4045.3007136121364 
4590          spin71.kC = 3586.38798270774 
4591   
4592          #self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
4593          #self.interpreter.minimise.grid_search(lower=None, upper=None, inc=41, constraints=True, verbosity=1) 
4594   
4595          # Low precision optimisation. 
4596          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None, max_iter=10000000, constraints=True, scaling=True, verbosity=1) 
4597   
4598          # Printout. 
4599          print("\n\nOptimised parameters:\n") 
4600          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4601          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4602          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4603          print("%-20s %20.15g %20.15g" % ("phi_ex_B", spin70.phi_ex_B, spin71.phi_ex_B)) 
4604          print("%-20s %20.15g %20.15g" % ("phi_ex_C", spin70.phi_ex_C, spin71.phi_ex_C)) 
4605          print("%-20s %20.15g %20.15g" % ("kB", spin70.kB, spin71.kB)) 
4606          print("%-20s %20.15g %20.15g" % ("kC", spin70.kC, spin71.kC)) 
4607          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4608   
4609          # Checks for residue :70. 
4610          self.assertAlmostEqual(spin70.r2[r20_key1], 6.7436230253685, 5) 
4611          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57406813008828, 6) 
4612          self.assertAlmostEqual(spin70.phi_ex_B, 0.206304023079778, 5) 
4613          self.assertAlmostEqual(spin70.phi_ex_C, 0.106428983339627, 5) 
4614          self.assertAlmostEqual(spin70.kB/1000, 4723.09897652589/1000, 6) 
4615          self.assertAlmostEqual(spin70.kC/1000, 4723.09876196409/1000, 6) 
4616          self.assertAlmostEqual(spin70.chi2, 363.534044873483, 5) 
4617   
4618          # Checks for residue :71. 
4619          self.assertAlmostEqual(spin71.r2[r20_key1], 4.96612095596752, 5) 
4620          self.assertAlmostEqual(spin71.phi_ex_B, 0.00398262266512895, 5) 
4621          self.assertAlmostEqual(spin71.phi_ex_C, 0.0555791581291262, 5) 
4622          self.assertAlmostEqual(spin71.kB/1000, 1323.33195689832/1000, 5) 
4623          self.assertAlmostEqual(spin71.kC/1000, 3149.58971568059/1000, 5) 
4624          self.assertAlmostEqual(spin71.chi2, 16.2620934464368) 
4625   
4626   
4627 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_3D(self): 
4628          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site 3D' dispersion model. 
4629   
4630          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4631          """ 
4632   
4633          # Base data setup. 
4634          self.setup_hansen_cpmg_data(model='NS CPMG 2-site 3D') 
4635   
4636          # Alias the spins. 
4637          spin70 = return_spin(":70") 
4638          spin71 = return_spin(":71") 
4639   
4640          # The R20 keys. 
4641          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4642          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4643   
4644          # Set the initial parameter values. 
4645          spin70.r2 = {r20_key1: 6.994165925, r20_key2: 9.428129427} 
4646          spin70.pA = 0.9897754407 
4647          spin70.dw = 5.642418428 
4648          spin70.kex = 1743.666375 
4649          spin71.r2 = {r20_key1: 4.978654237, r20_key2: 9.276918959} 
4650          spin71.pA = 0.9968032899 
4651          spin71.dw = 4.577891393 
4652          spin71.kex = 1830.044597 
4653   
4654          # Low precision optimisation. 
4655          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4656   
4657          # Printout. 
4658          print("\n\nOptimised parameters:\n") 
4659          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4660          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4661          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4662          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4663          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4664          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4665          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4666   
4667          # Checks for residue :70. 
4668          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95797760459016, 4) 
4669          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39628959312699, 4) 
4670          self.assertAlmostEqual(spin70.pA, 0.989700985380975, 4) 
4671          self.assertAlmostEqual(spin70.dw, 5.6733714171086, 4) 
4672          self.assertAlmostEqual(spin70.kex/1000, 1713.63101361545/1000, 4) 
4673          self.assertAlmostEqual(spin70.chi2, 52.5106928523775, 4) 
4674   
4675          # Checks for residue :71. 
4676          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99893565849977, 4) 
4677          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89825625944034, 4) 
4678          self.assertAlmostEqual(spin71.pA, 0.986716058519642, 4) 
4679          self.assertAlmostEqual(spin71.dw, 2.09292495350993, 4) 
4680          self.assertAlmostEqual(spin71.kex/1000, 2438.04423541463/1000, 4) 
4681          self.assertAlmostEqual(spin71.chi2, 15.164490242352, 4) 
4682   
4683          # Test the conversion to k_AB from kex and pA. 
4684          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4685          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4686   
4687          # Test the conversion to k_BA from kex and pA. 
4688          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4689          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4690   
4691   
4692 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_3D_full(self): 
4693          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site 3D full' dispersion model. 
4694   
4695          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4696          """ 
4697   
4698          # Base data setup. 
4699          self.setup_hansen_cpmg_data(model='NS CPMG 2-site 3D full') 
4700   
4701          # Alias the spins. 
4702          spin70 = return_spin(":70") 
4703          spin71 = return_spin(":71") 
4704   
4705          # The R20 keys. 
4706          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4707          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4708   
4709          # Set the initial parameter values. 
4710          spin70.r2a = {r20_key1: 6.644753428, r20_key2: 7.891776687} 
4711          spin70.r2b = {r20_key1: 7.163478485, r20_key2: 138.5170395} 
4712          spin70.pA = 0.9884781357 
4713          spin70.dw = 5.456507396 
4714          spin70.kex = 1906.521189 
4715          spin71.r2a = {r20_key1: 4.99893524108981, r20_key2: 100.0} 
4716          spin71.r2b = {r20_key1: 8.27456243639973, r20_key2: 100.0} 
4717          spin71.pA = 0.986709616684097 
4718          spin71.dw = 2.09245158280905 
4719          spin71.kex = 2438.2766211401 
4720   
4721          # Low precision optimisation. 
4722          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4723   
4724          # Printout. 
4725          print("\n\nOptimised parameters:\n") 
4726          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4727          print("%-20s %20.15g %20.15g" % ("R2A (500 MHz)", spin70.r2a[r20_key1], spin71.r2a[r20_key1])) 
4728          print("%-20s %20.15g %20.15g" % ("R2B (500 MHz)", spin70.r2b[r20_key1], spin71.r2b[r20_key1])) 
4729          print("%-20s %20.15g %20.15g" % ("R2A (800 MHz)", spin70.r2a[r20_key2], spin71.r2a[r20_key2])) 
4730          print("%-20s %20.15g %20.15g" % ("R2B (800 MHz)", spin70.r2b[r20_key2], spin71.r2b[r20_key2])) 
4731          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4732          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4733          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4734          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4735   
4736          # Checks for residue :70. 
4737          self.assertAlmostEqual(spin70.r2a[r20_key1], 6.61176004043484, 4) 
4738          self.assertAlmostEqual(spin70.r2b[r20_key1], 7.4869316381241, 4) 
4739          self.assertAlmostEqual(spin70.r2a[r20_key2], 7.78200386067591, 4) 
4740          self.assertAlmostEqual(spin70.r2b[r20_key2], 141.703593742468, 4) 
4741          self.assertAlmostEqual(spin70.pA, 0.988404987055969, 4) 
4742          self.assertAlmostEqual(spin70.dw, 5.4497360203213, 4) 
4743          self.assertAlmostEqual(spin70.kex/1000, 1934.09304607082/1000, 4) 
4744          self.assertAlmostEqual(spin70.chi2, 44.6793752187925, 4) 
4745   
4746          # Checks for residue :71. 
4747          self.assertAlmostEqual(spin71.r2a[r20_key1], 4.6013095731966, 4) 
4748          self.assertAlmostEqual(spin71.r2b[r20_key1], 13.3245678276332, 4) 
4749          self.assertAlmostEqual(spin71.r2a[r20_key2], 2.08243621257779, 4) 
4750          self.assertAlmostEqual(spin71.r2b[r20_key2], 153.355765094575, 4) 
4751          self.assertAlmostEqual(spin71.pA, 0.9665748685124, 4) 
4752          self.assertAlmostEqual(spin71.dw, 1.41898001408953, 4) 
4753          self.assertAlmostEqual(spin71.kex/1000, 2580.65795560688/1000, 4) 
4754          self.assertAlmostEqual(spin71.chi2, 13.4937006732165, 4) 
4755   
4756          # Test the conversion to k_AB from kex and pA. 
4757          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4758          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4759   
4760          # Test the conversion to k_BA from kex and pA. 
4761          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4762          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4763   
4764   
4765 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_expanded(self): 
4766          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site expanded' dispersion model. 
4767   
4768          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4769          """ 
4770   
4771          # Base data setup. 
4772          self.setup_hansen_cpmg_data(model='NS CPMG 2-site expanded') 
4773   
4774          # Alias the spins. 
4775          spin70 = return_spin(":70") 
4776          spin71 = return_spin(":71") 
4777   
4778          # The R20 keys. 
4779          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4780          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4781   
4782          # Set the initial parameter values. 
4783          spin70.r2 = {r20_key1: 7.0, r20_key2: 9.0} 
4784          spin70.pA = 0.9 
4785          spin70.dw = 6.0 
4786          spin70.kex = 1500.0 
4787          spin71.r2 = {r20_key1: 5.0, r20_key2: 9.0} 
4788          spin71.pA = 0.9 
4789          spin71.dw = 4.0 
4790          spin71.kex = 1900.0 
4791   
4792          # Low precision optimisation. 
4793          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4794   
4795          # Printout. 
4796          print("\n\nOptimised parameters:\n") 
4797          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4798          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4799          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4800          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4801          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4802          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4803          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4804   
4805          # Checks for residue :70. 
4806          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95813330991529, 4) 
4807          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39663480561524, 4) 
4808          self.assertAlmostEqual(spin70.pA, 0.989700843879574, 4) 
4809          self.assertAlmostEqual(spin70.dw, 5.67315878825691, 4) 
4810          self.assertAlmostEqual(spin70.kex/1000, 1713.56110716632/1000, 4) 
4811          self.assertAlmostEqual(spin70.chi2, 52.5106879242812, 4) 
4812   
4813          # Checks for residue :71. 
4814          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99881666793312, 4) 
4815          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89817482453042, 4) 
4816          self.assertAlmostEqual(spin71.pA, 0.986712911453639, 4) 
4817          self.assertAlmostEqual(spin71.dw, 2.09273069372236, 4) 
4818          self.assertAlmostEqual(spin71.kex/1000, 2438.20525930405/1000, 4) 
4819          self.assertAlmostEqual(spin71.chi2, 15.1644913030633, 4) 
4820   
4821          # Test the conversion to k_AB from kex and pA. 
4822          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4823          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4824   
4825          # Test the conversion to k_BA from kex and pA. 
4826          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4827          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4828   
4829   
4830 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_star(self): 
4831          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site star' dispersion model. 
4832   
4833          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4834          """ 
4835   
4836          # Base data setup. 
4837          self.setup_hansen_cpmg_data(model='NS CPMG 2-site star') 
4838   
4839          # Alias the spins. 
4840          spin70 = return_spin(":70") 
4841          spin71 = return_spin(":71") 
4842   
4843          # The R20 keys. 
4844          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4845          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4846   
4847          # Set the initial parameter values. 
4848          spin70.r2 = {r20_key1: 6.996327746, r20_key2: 9.452051268} 
4849          spin70.pA = 0.9897519798 
4850          spin70.dw = 5.644862195 
4851          spin70.kex = 1723.820567 
4852          spin71.r2 = {r20_key1: 4.978654237, r20_key2: 9.276918959} 
4853          spin71.pA = 0.9968032899 
4854          spin71.dw = 4.577891393 
4855          spin71.kex = 1830.044597 
4856   
4857          # Low precision optimisation. 
4858          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4859   
4860          # Printout. 
4861          print("\n\nOptimised parameters:\n") 
4862          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4863          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4864          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4865          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4866          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4867          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4868          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4869   
4870          # Checks for residue :70. 
4871          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95543947938561, 1) 
4872          self.assertAlmostEqual(spin70.r2[r20_key2], 9.38991914134929, 1) 
4873          self.assertAlmostEqual(spin70.pA, 0.989702750971153, 3) 
4874          self.assertAlmostEqual(spin70.dw, 5.67527122494516, 1) 
4875          self.assertAlmostEqual(spin70.kex/1000, 1715.72032391817/1000, 1) 
4876          self.assertAlmostEqual(spin70.chi2, 52.5011991483842, 1) 
4877   
4878          # Checks for residue :71. 
4879          self.assertAlmostEqual(spin71.r2[r20_key1], 4.992594256544, 1) 
4880          self.assertAlmostEqual(spin71.pA, 0.986716058519642, 2) 
4881          self.assertAlmostEqual(spin71.dw/100, 2.09292495350993/100, 2) 
4882          self.assertAlmostEqual(spin71.kex/100000, 2438.04423541463/100000, 2) 
4883          self.assertAlmostEqual(spin71.chi2/100, 15.1644902423334/100, 1) 
4884   
4885          # Test the conversion to k_AB from kex and pA. 
4886          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4887          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4888   
4889          # Test the conversion to k_BA from kex and pA. 
4890          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4891          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4892   
4893   
4894 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_star_full(self): 
4895          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site star full' dispersion model. 
4896   
4897          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4898          """ 
4899   
4900          # Base data setup. 
4901          self.setup_hansen_cpmg_data(model='NS CPMG 2-site star full') 
4902   
4903          # Alias the spins. 
4904          spin70 = return_spin(":70") 
4905          spin71 = return_spin(":71") 
4906   
4907          # The R20 keys. 
4908          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4909          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4910   
4911          # Set the initial parameter values. 
4912          spin70.r2a = {r20_key1: 6.44836878645126, r20_key2: 7.00382877393494} 
4913          spin70.r2b = {r20_key1: 12.2083127421994, r20_key2: 199.862962628402} 
4914          spin70.pA = 0.987648082613451 
4915          spin70.dw = 5.30679853807572 
4916          spin70.kex = 2033.25380420666 
4917          spin71.r2a = {r20_key1: 4.992594256544, r20_key2: 6.98674718938435} 
4918          spin71.r2b = {r20_key1: 4.992594256544, r20_key2: 6.98674718938435} 
4919          spin71.pA = 0.992258541625787 
4920          spin71.dw = 2.75140650899058 
4921          spin71.kex = 2106.60885247431 
4922   
4923          # Low precision optimisation. 
4924          self.interpreter.minimise.calculate() 
4925   
4926          # Checks for residue :70. 
4927          self.assertAlmostEqual(spin70.chi2/10, 45.773987568491123/10, 2) 
4928          self.assertAlmostEqual(spin71.chi2/10, 17.329385665659192/10, 2) 
4929   
4930   
4931 -    def test_hansen_cpmgfit_input(self): 
4932          """Conversion of Dr. Flemming Hansen's CPMG R2eff values into input files for CPMGFit. 
4933   
4934          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4935          """ 
4936   
4937          # Load the R2eff results file. 
4938          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'r2eff_pipe' 
4939          self.interpreter.results.read(file_name) 
4940          self.interpreter.deselect.spin(':4') 
4941   
4942          # Set up the model. 
4943          self.interpreter.relax_disp.select_model('LM63') 
4944   
4945          # Generate the input files. 
4946          self.interpreter.relax_disp.cpmgfit_input(force=True, dir=ds.tmpdir) 
4947   
4948          # What the files should contain. 
4949          batch_file = ['#! /bin/sh\n', '\n', 'cpmgfit -grid -xmgr -f spin_70_N.in | tee spin_70_N.out\n', 'cpmgfit -grid -xmgr -f spin_71_N.in | tee spin_71_N.out\n'] 
4950          spin1 = [ 
4951              "title :70@N\n", 
4952              "fields 2 11.7432964915 18.7892743865\n", 
4953              "function CPMG\n", 
4954              "R2 1 10 20\n", 
4955              "Rex 0 100.0 100\n", 
4956              "Tau 0 10.0 100\n", 
4957              "xmgr\n", 
4958              "@ xaxis label \"1/tcp (1/ms)\"\n", 
4959              "@ yaxis label \"R2(tcp) (rad/s)\"\n", 
4960              "@ xaxis ticklabel format decimal\n", 
4961              "@ yaxis ticklabel format decimal\n", 
4962              "@ xaxis ticklabel char size 0.8\n", 
4963              "@ yaxis ticklabel char size 0.8\n", 
4964              "@ world xmin 0.0\n", 
4965              "data\n", 
4966              "0.133333             16.045541            0.310925             11.743296           \n", 
4967              "0.266667             14.877925            0.303217             11.743296           \n", 
4968              "0.400000             14.357820            0.299894             11.743296           \n", 
4969              "0.533333             12.664495            0.289532             11.743296           \n", 
4970              "0.666667             12.363205            0.287760             11.743296           \n", 
4971              "0.800000             11.092532            0.280514             11.743296           \n", 
4972              "0.933333             10.566090            0.277619             11.743296           \n", 
4973              "1.066667             9.805807             0.273544             11.743296           \n", 
4974              "1.200000             9.564301             0.272276             11.743296           \n", 
4975              "1.333333             9.015634             0.269442             11.743296           \n", 
4976              "1.466667             8.607765             0.267375             11.743296           \n", 
4977              "1.600000             8.279997             0.265740             11.743296           \n", 
4978              "1.733333             8.474536             0.266708             11.743296           \n", 
4979              "1.866667             8.158973             0.265141             11.743296           \n", 
4980              "2.000000             7.988631             0.264304             11.743296           \n", 
4981              "0.133333             22.224914            0.166231             18.789274           \n", 
4982              "0.266667             21.230874            0.162377             18.789274           \n", 
4983              "0.400000             20.603704            0.160017             18.789274           \n", 
4984              "0.533333             20.327797            0.158996             18.789274           \n", 
4985              "0.666667             18.855377            0.153719             18.789274           \n", 
4986              "0.800000             18.537531            0.152617             18.789274           \n", 
4987              "0.933333             17.508069            0.149138             18.789274           \n", 
4988              "1.066667             16.035604            0.144391             18.789274           \n", 
4989              "1.200000             15.168192            0.141717             18.789274           \n", 
4990              "1.333333             14.431802            0.139516             18.789274           \n", 
4991              "1.466667             14.034137            0.138354             18.789274           \n", 
4992              "1.600000             12.920148            0.135192             18.789274           \n", 
4993              "1.733333             12.653673            0.134456             18.789274           \n", 
4994              "1.866667             12.610864            0.134338             18.789274           \n", 
4995              "2.000000             11.969303            0.132601             18.789274           \n" 
4996          ] 
4997          spin2 = [ 
4998              "title :71@N\n", 
4999              "fields 2 11.7432964915 18.7892743865\n", 
5000              "function CPMG\n", 
5001              "R2 1 10 20\n", 
5002              "Rex 0 100.0 100\n", 
5003              "Tau 0 10.0 100\n", 
5004              "xmgr\n", 
5005              "@ xaxis label \"1/tcp (1/ms)\"\n", 
5006              "@ yaxis label \"R2(tcp) (rad/s)\"\n", 
5007              "@ xaxis ticklabel format decimal\n", 
5008              "@ yaxis ticklabel format decimal\n", 
5009              "@ xaxis ticklabel char size 0.8\n", 
5010              "@ yaxis ticklabel char size 0.8\n", 
5011              "@ world xmin 0.0\n", 
5012              "data\n", 
5013              "0.133333             7.044342             0.170035             11.743296           \n", 
5014              "0.266667             6.781033             0.169228             11.743296           \n", 
5015              "0.400000             6.467623             0.168279             11.743296           \n", 
5016              "0.533333             6.333340             0.167876             11.743296           \n", 
5017              "0.666667             6.323238             0.167846             11.743296           \n", 
5018              "0.800000             6.005245             0.166902             11.743296           \n", 
5019              "0.933333             5.767052             0.166203             11.743296           \n", 
5020              "1.066667             5.476968             0.165361             11.743296           \n", 
5021              "1.200000             5.469949             0.165341             11.743296           \n", 
5022              "1.333333             5.295113             0.164838             11.743296           \n", 
5023              "1.466667             5.435648             0.165242             11.743296           \n", 
5024              "1.600000             5.410400             0.165169             11.743296           \n", 
5025              "1.733333             5.437554             0.165247             11.743296           \n", 
5026              "1.866667             5.176844             0.164501             11.743296           \n", 
5027              "2.000000             5.227232             0.164644             11.743296           \n", 
5028              "0.133333             11.530903            0.081928             18.789274           \n", 
5029              "0.266667             10.983094            0.081041             18.789274           \n", 
5030              "0.400000             10.512403            0.080294             18.789274           \n", 
5031              "0.533333             9.984805             0.079473             18.789274           \n", 
5032              "0.666667             9.573163             0.078845             18.789274           \n", 
5033              "0.800000             9.178810             0.078253             18.789274           \n", 
5034              "0.933333             8.935719             0.077893             18.789274           \n", 
5035              "1.066667             8.610147             0.077416             18.789274           \n", 
5036              "1.200000             8.353778             0.077045             18.789274           \n", 
5037              "1.333333             8.173729             0.076787             18.789274           \n", 
5038              "1.466667             8.091607             0.076670             18.789274           \n", 
5039              "1.600000             7.706420             0.076126             18.789274           \n", 
5040              "1.733333             7.709125             0.076129             18.789274           \n", 
5041              "1.866667             7.610856             0.075992             18.789274           \n", 
5042              "2.000000             7.552584             0.075911             18.789274           \n", 
5043          ] 
5044   
5045          # Check the batch file. 
5046          print("\nChecking the batch file.") 
5047          file = open("%s%sbatch_run.sh" % (ds.tmpdir, sep)) 
5048          lines = file.readlines() 
5049          file.close() 
5050          for i in range(len(lines)): 
5051              self.assertEqual(batch_file[i], lines[i]) 
5052   
5053          # Check spin :70@N. 
5054          print("\nChecking the spin :70@N input file.") 
5055          file = open("%s%sspin%s.in" % (ds.tmpdir, sep, '_70_N')) 
5056          lines = file.readlines() 
5057          file.close() 
5058          for i in range(len(spin1)): 
5059              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
5060          for i in range(len(lines)): 
5061              self.assertEqual(spin1[i], lines[i]) 
5062   
5063          # Check spin :71@N. 
5064          print("\nChecking the spin :71@N input file.") 
5065          file = open("%s%sspin%s.in" % (ds.tmpdir, sep, '_71_N')) 
5066          lines = file.readlines() 
5067          file.close() 
5068          for i in range(len(lines)): 
5069              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
5070          for i in range(len(spin2)): 
5071              self.assertEqual(spin2[i], lines[i]) 
5072   
5073   
5074 -    def test_korzhnev_2005_15n_dq_data(self): 
5075          """Optimisation of the Korzhnev et al., 2005 15N DQ CPMG data using the 'NS MMQ 2-site' model. 
5076   
5077          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5078   
5079          Here only the 15N DQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5080   
5081              - r2 = {'500': 9.487269007171426, '600': 11.718267257562591, '800': 13.624551743116887}, 
5082              - pA = 0.965402506690231, 
5083              - dw = 0.805197170133360, 
5084              - dwH = -0.595536627771890, 
5085              - kex = 569.003663067619868, 
5086              - chi2 = 9.297671357952812. 
5087          """ 
5088   
5089          # Base data setup. 
5090          self.setup_korzhnev_2005_data(data_list=['DQ']) 
5091   
5092          # Alias the spin. 
5093          spin = return_spin(":9@N") 
5094   
5095          # The R20 keys. 
5096          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5097          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5098          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5099   
5100          # Set the initial parameter values. 
5101          spin.r2 = {r20_key1: 9.48527908326952, r20_key2: 11.7135951595536, r20_key3: 13.6153887849344} 
5102          spin.pA = 0.965638501551899 
5103          spin.dw = 2.8537583461577 
5104          spin.dwH = -0.387633062766635 
5105          spin.kex = 573.704033851592 
5106   
5107          # Low precision optimisation. 
5108          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5109   
5110          # Monte Carlo simulations. 
5111          self.interpreter.monte_carlo.setup(number=3) 
5112          self.interpreter.monte_carlo.create_data(method='back_calc') 
5113          self.interpreter.monte_carlo.initial_values() 
5114          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5115          self.interpreter.monte_carlo.error_analysis() 
5116   
5117          # Plot the dispersion curves. 
5118          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5119   
5120          # Save the results. 
5121          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5122   
5123          # Printout. 
5124          print("\n\nOptimised parameters:\n") 
5125          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5126          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5127          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5128          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5129          print("%-20s %20.15g" % ("pA", spin.pA)) 
5130          print("%-20s %20.15g" % ("dw", spin.dw)) 
5131          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5132          print("%-20s %20.15g" % ("kex", spin.kex)) 
5133          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5134   
5135          # Checks for residue :9. 
5136          self.assertAlmostEqual(spin.r2[r20_key1], 9.4870656457415, 2) 
5137          self.assertAlmostEqual(spin.r2[r20_key2], 11.7183291788929, 2) 
5138          self.assertAlmostEqual(spin.r2[r20_key3], 13.6241729933153, 2) 
5139          self.assertAlmostEqual(spin.pA, 0.965405468217295, 4) 
5140          self.assertAlmostEqual(spin.dw, 2.76835528427355, 1) 
5141          self.assertAlmostEqual(spin.dwH, -0.396489341086363, 2) 
5142          self.assertAlmostEqual(spin.kex/1000, 569.06937047601/1000, 3) 
5143          self.assertAlmostEqual(spin.chi2, 9.29767487125257, 2) 
5144   
5145   
5146 -    def test_korzhnev_2005_15n_mq_data(self): 
5147          """Optimisation of the Korzhnev et al., 2005 15N MQ CPMG data using the 'NS MMQ 2-site' model. 
5148   
5149          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5150   
5151          Here only the 15N MQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5152   
5153              - r2 = {'500': 5.993083514798655, '600': 6.622184438384841, '800': 8.640765919352019}, 
5154              - pA = 0.930027999814003, 
5155              - dw = 4.338620619954370, 
5156              - dwH = -0.274250775560818, 
5157              - kex = 344.613362916544475, 
5158              - chi2 = 10.367733168217050. 
5159          """ 
5160   
5161          # Base data setup. 
5162          self.setup_korzhnev_2005_data(data_list=['MQ']) 
5163   
5164          # Alias the spin. 
5165          spin = return_spin(":9@N") 
5166   
5167          # The R20 keys. 
5168          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5169          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5170          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5171   
5172          # Set the initial parameter values. 
5173          spin.r2 = {r20_key1: 6.02016436619016, r20_key2: 6.65421500772308, r20_key3: 8.6729591487622} 
5174          spin.pA = 0.930083249288083 
5175          spin.dw = 4.33890689462363 
5176          spin.dwH = -0.274316585638047 
5177          spin.kex = 344.329651956132 
5178   
5179          # Low precision optimisation. 
5180          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5181   
5182          # Monte Carlo simulations. 
5183          self.interpreter.monte_carlo.setup(number=3) 
5184          self.interpreter.monte_carlo.create_data(method='back_calc') 
5185          self.interpreter.monte_carlo.initial_values() 
5186          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5187          self.interpreter.monte_carlo.error_analysis() 
5188   
5189          # Plot the dispersion curves. 
5190          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5191   
5192          # Save the results. 
5193          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5194   
5195          # Printout. 
5196          print("\n\nOptimised parameters:\n") 
5197          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5198          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5199          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5200          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5201          print("%-20s %20.15g" % ("pA", spin.pA)) 
5202          print("%-20s %20.15g" % ("dw", spin.dw)) 
5203          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5204          print("%-20s %20.15g" % ("kex", spin.kex)) 
5205          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5206   
5207          # Checks for residue :9. 
5208          self.assertAlmostEqual(spin.r2[r20_key1], 5.99503641023038, 1) 
5209          self.assertAlmostEqual(spin.r2[r20_key2], 6.62432897608527, 1) 
5210          self.assertAlmostEqual(spin.r2[r20_key3], 8.64278915809492, 1) 
5211          self.assertAlmostEqual(spin.pA, 0.930036474040713, 3) 
5212          self.assertAlmostEqual(spin.dw, 4.33848403058432, 2) 
5213          self.assertAlmostEqual(spin.dwH, -0.274246558825267, 3) 
5214          self.assertAlmostEqual(spin.kex/1000, 344.626563267384/1000, 3) 
5215          self.assertAlmostEqual(spin.chi2, 10.3677362372789, 2) 
5216   
5217   
5218 -    def test_korzhnev_2005_15n_sq_data(self): 
5219          """Optimisation of the Korzhnev et al., 2005 15N SQ CPMG data using the 'NS MMQ 2-site' model. 
5220   
5221          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5222   
5223          Here only the 15N SQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5224   
5225              - r2 = {'500': 8.335037972570017, '600': 8.761366016417508, '800': 10.225001019091822}, 
5226              - pA = 0.950003458294991, 
5227              - dw = 4.358402855315123, 
5228              - kex = 429.906473361926999, 
5229              - chi2 = 17.393331915567252. 
5230          """ 
5231   
5232          # Base data setup. 
5233          self.setup_korzhnev_2005_data(data_list=['SQ']) 
5234   
5235          # Alias the spin. 
5236          spin = return_spin(":9@N") 
5237   
5238          # The R20 keys. 
5239          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5240          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5241          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5242   
5243          # Set the initial parameter values. 
5244          spin.r2 = {r20_key1: 8.334232330326190, r20_key2: 8.756773997879968, r20_key3: 10.219320492033058} 
5245          spin.pA = 0.950310172115387 
5246          spin.dw = 4.356737157889636 
5247          spin.kex = 433.176323890829849 
5248   
5249          # Low precision optimisation. 
5250          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5251   
5252          # Monte Carlo simulations. 
5253          self.interpreter.monte_carlo.setup(number=3) 
5254          self.interpreter.monte_carlo.create_data(method='back_calc') 
5255          self.interpreter.monte_carlo.initial_values() 
5256          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5257          self.interpreter.monte_carlo.error_analysis() 
5258   
5259          # Plot the dispersion curves. 
5260          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5261   
5262          # Save the results. 
5263          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5264   
5265          # Printout. 
5266          print("\n\nOptimised parameters:\n") 
5267          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5268          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5269          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5270          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5271          print("%-20s %20.15g" % ("pA", spin.pA)) 
5272          print("%-20s %20.15g" % ("dw", spin.dw)) 
5273          print("%-20s %20.15g" % ("kex", spin.kex)) 
5274          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5275   
5276          # Checks for residue :9. 
5277          self.assertAlmostEqual(spin.r2[r20_key1], 8.33499994313902, 2) 
5278          self.assertAlmostEqual(spin.r2[r20_key2], 8.76118738798082, 2) 
5279          self.assertAlmostEqual(spin.r2[r20_key3], 10.2250821829928, 1) 
5280          self.assertAlmostEqual(spin.pA, 0.950000281516303, 3) 
5281          self.assertAlmostEqual(spin.dw, 4.35845318983581, 2) 
5282          self.assertAlmostEqual(spin.kex/1000, 429.874510184149/1000, 2) 
5283          self.assertAlmostEqual(spin.chi2, 17.3933357984425, 1) 
5284   
5285   
5286 -    def test_korzhnev_2005_15n_zq_data(self): 
5287          """Optimisation of the Korzhnev et al., 2005 15N ZQ CPMG data using the 'NS MMQ 2-site' model. 
5288   
5289          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5290   
5291          Here only the 15N ZQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5292   
5293              - r2 = {'500': 5.909812628572937, '600': 6.663690132557320, '800': 6.787171647689906}, 
5294              - pA = 0.942452612380140, 
5295              - dw = 0.858972784230892, 
5296              - dwH = 0.087155962730608, 
5297              - kex = 373.219151384798920, 
5298              - chi2 = 23.863208106025152. 
5299          """ 
5300   
5301          # Base data setup. 
5302          self.setup_korzhnev_2005_data(data_list=['ZQ']) 
5303   
5304          # Alias the spin. 
5305          spin = return_spin(":9@N") 
5306   
5307          # The R20 keys. 
5308          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5309          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5310          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5311   
5312          # Set the initial parameter values. 
5313          spin.r2 = {r20_key1: 5.91033272691614, r20_key2: 6.66368695342258, r20_key3: 6.78922219135537} 
5314          spin.pA = 0.942457332074014 
5315          spin.dw = 0.850592422908884 
5316          spin.dwH = 0.0881272284455416 
5317          spin.kex = 372.745483351305 
5318   
5319          # Low precision optimisation. 
5320          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5321   
5322          # Monte Carlo simulations. 
5323          self.interpreter.monte_carlo.setup(number=3) 
5324          self.interpreter.monte_carlo.create_data(method='back_calc') 
5325          self.interpreter.monte_carlo.initial_values() 
5326          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5327          self.interpreter.monte_carlo.error_analysis() 
5328   
5329          # Plot the dispersion curves. 
5330          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5331   
5332          # Save the results. 
5333          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5334   
5335          # Printout. 
5336          print("\n\nOptimised parameters:\n") 
5337          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5338          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5339          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5340          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5341          print("%-20s %20.15g" % ("pA", spin.pA)) 
5342          print("%-20s %20.15g" % ("dw", spin.dw)) 
5343          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5344          print("%-20s %20.15g" % ("kex", spin.kex)) 
5345          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5346   
5347          # Checks for residue :9. 
5348          self.assertAlmostEqual(spin.r2[r20_key1], 5.9098385837035, 2) 
5349          self.assertAlmostEqual(spin.r2[r20_key2], 6.66377885876553, 2) 
5350          self.assertAlmostEqual(spin.r2[r20_key3], 6.78717432941353, 2) 
5351          self.assertAlmostEqual(spin.pA, 0.942457141344462, 4) 
5352          self.assertAlmostEqual(spin.dw, 0.84442055695814, 1) 
5353          self.assertAlmostEqual(spin.dwH, 0.0886367674566058, 2) 
5354          self.assertAlmostEqual(spin.kex/1000, 373.243053643367/1000, 3) 
5355          self.assertAlmostEqual(spin.chi2, 23.863211604121, 1) 
5356   
5357   
5358 -    def test_korzhnev_2005_1h_mq_data(self): 
5359          """Optimisation of the Korzhnev et al., 2005 1H MQ CPMG data using the 'NS MMQ 2-site' model. 
5360   
5361          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5362   
5363          Here only the 1H MQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5364   
5365              - r2 = {'500': -0.000016676911302, '600': 0.036594127620440, '800': 2.131014839635728}, 
5366              - pA = 0.936911090448340, 
5367              - dw = 4.325314846914845, 
5368              - dwH = -0.213870168665628, 
5369              - kex = 487.361914835074117, 
5370              - chi2 = 14.870371897291138. 
5371          """ 
5372   
5373          # Base data setup. 
5374          self.setup_korzhnev_2005_data(data_list=['1H MQ']) 
5375   
5376          # Alias the spin. 
5377          spin = return_spin(":9@N") 
5378   
5379          # The R20 keys. 
5380          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5381          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5382          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5383   
5384          # Set the initial parameter values. 
5385          spin.r2 = {r20_key1: 0.000022585022901, r20_key2: 0.039223196112941, r20_key3: 2.136576686700357} 
5386          spin.pA = 0.936884348941701 
5387          spin.dw = 4.326454531583964 
5388          spin.dwH = -0.214026093221782 
5389          spin.kex = 487.043592705469223 
5390   
5391          # Low precision optimisation. 
5392          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=100) 
5393   
5394          # Monte Carlo simulations. 
5395          self.interpreter.monte_carlo.setup(number=3) 
5396          self.interpreter.monte_carlo.create_data(method='back_calc') 
5397          self.interpreter.monte_carlo.initial_values() 
5398          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5399          self.interpreter.monte_carlo.error_analysis() 
5400   
5401          # Plot the dispersion curves. 
5402          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5403   
5404          # Save the results. 
5405          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5406   
5407          # Printout. 
5408          print("\n\nOptimised parameters:\n") 
5409          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5410          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5411          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5412          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5413          print("%-20s %20.15g" % ("pA", spin.pA)) 
5414          print("%-20s %20.15g" % ("dw", spin.dw)) 
5415          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5416          print("%-20s %20.15g" % ("kex", spin.kex)) 
5417          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5418   
5419          # Checks for residue :9. 
5420          self.assertAlmostEqual(spin.r2[r20_key1], 2.48493199969936e-05, 4) 
5421          self.assertAlmostEqual(spin.r2[r20_key2], 0.0382382195911849, 2) 
5422          self.assertAlmostEqual(spin.r2[r20_key3], 2.13397221524655, 2) 
5423          self.assertAlmostEqual(spin.pA, 0.936879359956996, 4) 
5424          self.assertAlmostEqual(spin.dw, 4.32573362253701, 2) 
5425          self.assertAlmostEqual(spin.dwH, -0.213951762275293, 2) 
5426          self.assertAlmostEqual(spin.kex/1000, 487.021196851596/1000, 4) 
5427          self.assertAlmostEqual(spin.chi2, 14.8704048958378, 2) 
5428   
5429   
5430 -    def test_korzhnev_2005_1h_sq_data(self): 
5431          """Optimisation of the Korzhnev et al., 2005 1H SQ CPMG data using the 'NS MMQ 2-site' model. 
5432   
5433          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5434   
5435          Here only the 1H SQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5436   
5437              - r2 = {'500': 6.691697587650816, '600': 6.998915158708793, '800': 5.519267837559072}, 
5438              - pA = 0.946949480545876, 
5439              - dwH = -0.265279672133308, 
5440              - kex = 406.548178869750700, 
5441              - chi2 = 50.400680290545026. 
5442          """ 
5443   
5444          # Base data setup. 
5445          self.setup_korzhnev_2005_data(data_list=['1H SQ']) 
5446   
5447          # Alias the spin. 
5448          spin = return_spin(":9@N") 
5449   
5450          # The R20 keys. 
5451          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5452          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5453          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5454   
5455          # Set the initial parameter values. 
5456          spin.r2 = {r20_key1: 6.69107911078939, r20_key2: 6.99888898689085, r20_key3: 5.52012880268077} 
5457          spin.pA = 0.946990967372467 
5458          spin.dwH = -0.265308128403529 
5459          spin.kex = 406.843250675648 
5460   
5461          # Low precision optimisation. 
5462          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5463   
5464          # Monte Carlo simulations. 
5465          self.interpreter.monte_carlo.setup(number=3) 
5466          self.interpreter.monte_carlo.create_data(method='back_calc') 
5467          self.interpreter.monte_carlo.initial_values() 
5468          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5469          self.interpreter.monte_carlo.error_analysis() 
5470   
5471          # Plot the dispersion curves. 
5472          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5473   
5474          # Save the results. 
5475          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5476   
5477          # Printout. 
5478          print("\n\nOptimised parameters:\n") 
5479          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5480          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5481          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5482          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5483          print("%-20s %20.15g" % ("pA", spin.pA)) 
5484          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5485          print("%-20s %20.15g" % ("kex", spin.kex)) 
5486          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5487   
5488          # Checks for residue :9. 
5489          self.assertAlmostEqual(spin.r2[r20_key1], 6.69168251154302, 2) 
5490          self.assertAlmostEqual(spin.r2[r20_key2], 6.99900388754043, 2) 
5491          self.assertAlmostEqual(spin.r2[r20_key3], 5.51921590064843, 2) 
5492          self.assertAlmostEqual(spin.pA, 0.946951877648819, 4) 
5493          self.assertAlmostEqual(spin.dwH, -0.265280175525516, 3) 
5494          self.assertAlmostEqual(spin.kex/1000, 406.566453278183/1000, 2) 
5495          self.assertAlmostEqual(spin.chi2, 50.4006836222044, 1) 
5496   
5497   
5498 -    def test_korzhnev_2005_all_data(self): 
5499          """Optimisation of all the Korzhnev et al., 2005 CPMG data using the 'NS MMQ 2-site' model. 
5500   
5501          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5502   
5503          Here all data will be optimised.  The values found by cpmg_fit using just this data are: 
5504   
5505              - r2 = {'H-S 500':  6.671649051677150, 'H-S 600':  6.988634195648529, 'H-S 800':  5.527971316790596, 
5506                      'N-S 500':  8.394988400015988, 'N-S 600':  8.891359568401835, 'N-S 800': 10.405356669006709, 
5507                      'NHZ 500':  5.936446687394352, 'NHZ 600':  6.717058062814535, 'NHZ 800':  6.838733853403030, 
5508                      'NHD 500':  8.593136215779710, 'NHD 600': 10.651511259239674, 'NHD 800': 12.567902357560627, 
5509                      'HNM 500':  7.851325614877817, 'HNM 600':  8.408803624020202, 'HNM 800': 11.227489645758979, 
5510                      'NHM 500':  9.189159145380575, 'NHM 600':  9.856814478405868, 'NHM 800': 11.967910041807118}, 
5511              - pA = 0.943125351763911, 
5512              - dw = 4.421827493809807, 
5513              - dwH = -0.272637034755752, 
5514              - kex = 360.609744568697238, 
5515              - chi2 = 162.589570340050813. 
5516          """ 
5517   
5518          # Base data setup. 
5519          self.setup_korzhnev_2005_data(data_list=['SQ', '1H SQ', 'DQ', 'ZQ', 'MQ', '1H MQ']) 
5520   
5521          # Alias the spin. 
5522          spin = return_spin(":9@N") 
5523   
5524          # The R20 keys. 
5525          r20_key1  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5526          r20_key2  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5527          r20_key3  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5528          r20_key4  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5529          r20_key5  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5530          r20_key6  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5531          r20_key7  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5532          r20_key8  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5533          r20_key9  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5534          r20_key10 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5535          r20_key11 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5536          r20_key12 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5537          r20_key13 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5538          r20_key14 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5539          r20_key15 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5540          r20_key16 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5541          r20_key17 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5542          r20_key18 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5543   
5544          # Set the initial parameter values. 
5545          spin.r2 = { 
5546              r20_key1:   6.67288025927458, r20_key2:   6.98951408255098, r20_key3:   5.52959273852704, 
5547              r20_key4:   8.39471048876782, r20_key5:   8.89290699178799, r20_key6:  10.40770687236930, 
5548              r20_key7:   5.93611174376373, r20_key8:   6.71735669582514, r20_key9:   6.83835225518265, 
5549              r20_key10:  8.59615074668922, r20_key11: 10.65121378892910, r20_key12: 12.57108229191090, 
5550              r20_key13:  7.85956711501608, r20_key14:  8.41891642907918, r20_key15: 11.23620892230380, 
5551              r20_key16:  9.19654863789350, r20_key17:  9.86031627358462, r20_key18: 11.97523755925750 
5552          } 
5553          spin.pA = 0.943129019477673 
5554          spin.dw = 4.42209952545181 
5555          spin.dwH = -0.27258970590969 
5556          spin.kex = 360.516132791038 
5557   
5558          # Low precision optimisation. 
5559          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=10) 
5560   
5561          # Monte Carlo simulations. 
5562          self.interpreter.monte_carlo.setup(number=3) 
5563          self.interpreter.monte_carlo.create_data(method='back_calc') 
5564          self.interpreter.monte_carlo.initial_values() 
5565          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5566          self.interpreter.monte_carlo.error_analysis() 
5567   
5568          # Plot the dispersion curves. 
5569          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5570   
5571          # Save the results. 
5572          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5573   
5574          # Printout. 
5575          print("\n\nOptimised parameters:\n") 
5576          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5577          print("%-20s %20.15g" % ("R2 (1H SQ - 500 MHz)", spin.r2[r20_key1])) 
5578          print("%-20s %20.15g" % ("R2 (1H SQ - 600 MHz)", spin.r2[r20_key2])) 
5579          print("%-20s %20.15g" % ("R2 (1H SQ - 800 MHz)", spin.r2[r20_key3])) 
5580          print("%-20s %20.15g" % ("R2 (SQ - 500 MHz)", spin.r2[r20_key4])) 
5581          print("%-20s %20.15g" % ("R2 (SQ - 600 MHz)", spin.r2[r20_key5])) 
5582          print("%-20s %20.15g" % ("R2 (SQ - 800 MHz)", spin.r2[r20_key6])) 
5583          print("%-20s %20.15g" % ("R2 (ZQ - 500 MHz)", spin.r2[r20_key7])) 
5584          print("%-20s %20.15g" % ("R2 (ZQ - 600 MHz)", spin.r2[r20_key8])) 
5585          print("%-20s %20.15g" % ("R2 (ZQ - 800 MHz)", spin.r2[r20_key9])) 
5586          print("%-20s %20.15g" % ("R2 (DQ - 500 MHz)", spin.r2[r20_key10])) 
5587          print("%-20s %20.15g" % ("R2 (DQ - 600 MHz)", spin.r2[r20_key11])) 
5588          print("%-20s %20.15g" % ("R2 (DQ - 800 MHz)", spin.r2[r20_key12])) 
5589          print("%-20s %20.15g" % ("R2 (1H MQ - 500 MHz)", spin.r2[r20_key13])) 
5590          print("%-20s %20.15g" % ("R2 (1H MQ - 600 MHz)", spin.r2[r20_key14])) 
5591          print("%-20s %20.15g" % ("R2 (1H MQ - 800 MHz)", spin.r2[r20_key15])) 
5592          print("%-20s %20.15g" % ("R2 (MQ - 500 MHz)", spin.r2[r20_key16])) 
5593          print("%-20s %20.15g" % ("R2 (MQ - 600 MHz)", spin.r2[r20_key17])) 
5594          print("%-20s %20.15g" % ("R2 (MQ - 800 MHz)", spin.r2[r20_key18])) 
5595          print("%-20s %20.15g" % ("pA", spin.pA)) 
5596          print("%-20s %20.15g" % ("dw", spin.dw)) 
5597          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5598          print("%-20s %20.15g" % ("kex", spin.kex)) 
5599          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5600   
5601          # Checks for residue :9. 
5602          self.assertAlmostEqual(spin.r2[r20_key1],  6.67288025927458, 4) 
5603          self.assertAlmostEqual(spin.r2[r20_key2],  6.98951408255098, 4) 
5604          self.assertAlmostEqual(spin.r2[r20_key3],  5.52959273852704, 4) 
5605          self.assertAlmostEqual(spin.r2[r20_key4],  8.39471048876782, 4) 
5606          self.assertAlmostEqual(spin.r2[r20_key5],  8.89290699178799, 4) 
5607          self.assertAlmostEqual(spin.r2[r20_key6],  10.4077068723693, 4) 
5608          self.assertAlmostEqual(spin.r2[r20_key7],  5.93611174376373, 4) 
5609          self.assertAlmostEqual(spin.r2[r20_key8],  6.71735669582514, 4) 
5610          self.assertAlmostEqual(spin.r2[r20_key9],  6.83835225518265, 4) 
5611          self.assertAlmostEqual(spin.r2[r20_key10], 8.59615074668922, 4) 
5612          self.assertAlmostEqual(spin.r2[r20_key11], 10.6512137889291, 4) 
5613          self.assertAlmostEqual(spin.r2[r20_key12], 12.5710822919109, 4) 
5614          self.assertAlmostEqual(spin.r2[r20_key13], 7.85956711501608, 4) 
5615          self.assertAlmostEqual(spin.r2[r20_key14], 8.41891642907918, 4) 
5616          self.assertAlmostEqual(spin.r2[r20_key15], 11.2362089223038, 4) 
5617          self.assertAlmostEqual(spin.r2[r20_key16], 9.1965486378935, 4) 
5618          self.assertAlmostEqual(spin.r2[r20_key17], 9.86031627358462, 4) 
5619          self.assertAlmostEqual(spin.r2[r20_key18], 11.9752375592575, 4) 
5620          self.assertAlmostEqual(spin.pA, 0.943129019477673, 4) 
5621          self.assertAlmostEqual(spin.dw, 4.42209952545181, 4) 
5622          self.assertAlmostEqual(spin.dwH, -0.27258970590969, 4) 
5623          self.assertAlmostEqual(spin.kex/1000, 360.516132791038/1000, 4) 
5624          self.assertAlmostEqual(spin.chi2/1000, 162.596331278669/1000, 3) 
5625   
5626   
5627 -    def test_korzhnev_2005_all_data_disp_speed_bug(self): 
5628          """Optimisation of all the Korzhnev et al., 2005 CPMG data using the 'NS MMQ 2-site' model. 
5629   
5630          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5631   
5632          Here all data will be optimised.  The values found by cpmg_fit using just this data are: 
5633   
5634              - r2 = {'H-S 500':  6.671649051677150, 'H-S 600':  6.988634195648529, 'H-S 800':  5.527971316790596, 
5635                      'N-S 500':  8.394988400015988, 'N-S 600':  8.891359568401835, 'N-S 800': 10.405356669006709, 
5636                      'NHZ 500':  5.936446687394352, 'NHZ 600':  6.717058062814535, 'NHZ 800':  6.838733853403030, 
5637                      'NHD 500':  8.593136215779710, 'NHD 600': 10.651511259239674, 'NHD 800': 12.567902357560627, 
5638                      'HNM 500':  7.851325614877817, 'HNM 600':  8.408803624020202, 'HNM 800': 11.227489645758979, 
5639                      'NHM 500':  9.189159145380575, 'NHM 600':  9.856814478405868, 'NHM 800': 11.967910041807118}, 
5640              - pA = 0.943125351763911, 
5641              - dw = 4.421827493809807, 
5642              - dwH = -0.272637034755752, 
5643              - kex = 360.609744568697238, 
5644              - chi2 = 162.589570340050813. 
5645          """ 
5646   
5647          # Base data setup. 
5648          self.setup_korzhnev_2005_data(data_list=['SQ', '1H SQ', 'DQ', 'ZQ', 'MQ', '1H MQ']) 
5649   
5650          # Alias the spin. 
5651          spin = return_spin(":9@N") 
5652   
5653          # The R20 keys. 
5654          r20_key1  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5655          r20_key2  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5656          r20_key3  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5657          r20_key4  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5658          r20_key5  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5659          r20_key6  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5660          r20_key7  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5661          r20_key8  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5662          r20_key9  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5663          r20_key10 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5664          r20_key11 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5665          r20_key12 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5666          r20_key13 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5667          r20_key14 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5668          r20_key15 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5669          r20_key16 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5670          r20_key17 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5671          r20_key18 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5672   
5673          # Set the initial parameter values. 
5674          spin.r2 = { 
5675              r20_key1:   6.67288025927458, r20_key2:   6.98951408255098, r20_key3:   5.52959273852704, 
5676              r20_key4:   8.39471048876782, r20_key5:   8.89290699178799, r20_key6:  10.40770687236930, 
5677              r20_key7:   5.93611174376373, r20_key8:   6.71735669582514, r20_key9:   6.83835225518265, 
5678              r20_key10:  8.59615074668922, r20_key11: 10.65121378892910, r20_key12: 12.57108229191090, 
5679              r20_key13:  7.85956711501608, r20_key14:  8.41891642907918, r20_key15: 11.23620892230380, 
5680              r20_key16:  9.19654863789350, r20_key17:  9.86031627358462, r20_key18: 11.97523755925750 
5681          } 
5682          spin.pA = 0.943129019477673 
5683          spin.dw = 4.42209952545181 
5684          spin.dwH = -0.27258970590969 
5685          spin.kex = 360.516132791038 
5686   
5687          # Calc the chi2 values at these parameters. 
5688          self.interpreter.minimise.calculate(verbosity=1) 
5689   
5690          # Printout. 
5691          print("\n\nOptimised parameters:\n") 
5692          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5693          print("%-20s %20.15g" % ("R2 (1H SQ - 500 MHz)", spin.r2[r20_key1])) 
5694          print("%-20s %20.15g" % ("R2 (1H SQ - 600 MHz)", spin.r2[r20_key2])) 
5695          print("%-20s %20.15g" % ("R2 (1H SQ - 800 MHz)", spin.r2[r20_key3])) 
5696          print("%-20s %20.15g" % ("R2 (SQ - 500 MHz)", spin.r2[r20_key4])) 
5697          print("%-20s %20.15g" % ("R2 (SQ - 600 MHz)", spin.r2[r20_key5])) 
5698          print("%-20s %20.15g" % ("R2 (SQ - 800 MHz)", spin.r2[r20_key6])) 
5699          print("%-20s %20.15g" % ("R2 (ZQ - 500 MHz)", spin.r2[r20_key7])) 
5700          print("%-20s %20.15g" % ("R2 (ZQ - 600 MHz)", spin.r2[r20_key8])) 
5701          print("%-20s %20.15g" % ("R2 (ZQ - 800 MHz)", spin.r2[r20_key9])) 
5702          print("%-20s %20.15g" % ("R2 (DQ - 500 MHz)", spin.r2[r20_key10])) 
5703          print("%-20s %20.15g" % ("R2 (DQ - 600 MHz)", spin.r2[r20_key11])) 
5704          print("%-20s %20.15g" % ("R2 (DQ - 800 MHz)", spin.r2[r20_key12])) 
5705          print("%-20s %20.15g" % ("R2 (1H MQ - 500 MHz)", spin.r2[r20_key13])) 
5706          print("%-20s %20.15g" % ("R2 (1H MQ - 600 MHz)", spin.r2[r20_key14])) 
5707          print("%-20s %20.15g" % ("R2 (1H MQ - 800 MHz)", spin.r2[r20_key15])) 
5708          print("%-20s %20.15g" % ("R2 (MQ - 500 MHz)", spin.r2[r20_key16])) 
5709          print("%-20s %20.15g" % ("R2 (MQ - 600 MHz)", spin.r2[r20_key17])) 
5710          print("%-20s %20.15g" % ("R2 (MQ - 800 MHz)", spin.r2[r20_key18])) 
5711          print("%-20s %20.15g" % ("pA", spin.pA)) 
5712          print("%-20s %20.15g" % ("dw", spin.dw)) 
5713          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5714          print("%-20s %20.15g" % ("kex", spin.kex)) 
5715          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5716   
5717          # Checks for residue :9. 
5718          self.assertAlmostEqual(spin.chi2/1000, 162.511988511609/1000, 3) 
5719   
5720   
5721 -    def test_kteilum_fmpoulsen_makke_check_graphs(self): 
5722          """Check of all possible dispersion graphs from optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5723   
5724          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5725   
5726          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl. The precise values are: 
5727   
5728            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5729            - 0.483 0.89623903 2.4503699912708878 
5730            - 0.545 1.1694838 
5731            - 0.545 1.1761503 
5732            - 0.622 1.294 
5733            - 0.669 1.5176493 
5734            - 0.722 1.6238791 
5735            - 0.813 1.9395758 
5736            - 1.011 2.3558415 10.547000429321157 
5737          """ 
5738   
5739          # Base data setup. 
5740          model = 'TSMFK01' 
5741          expfolder = "acbp_cpmg_disp_048MGuHCl_40C_041223" 
5742          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model=model, expfolder=expfolder) 
5743   
5744          # Alias the spins. 
5745          res61L = cdp.mol[0].res[0].spin[0] 
5746   
5747          # The R20 keys. 
5748          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5749   
5750          # Set the initial parameter values. 
5751          res61L.r2a = {r20_key1: 8.0} 
5752          res61L.dw = 6.5 
5753          res61L.k_AB = 2.5 
5754   
5755          # Low precision optimisation. 
5756          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5757   
5758          # Start testing all possible combinations of graphs. 
5759          y_axis_types = [Y_AXIS_R2_EFF, Y_AXIS_R2_R1RHO] 
5760          x_axis_types = [X_AXIS_DISP, X_AXIS_THETA, X_AXIS_W_EFF] 
5761          interpolate_types = [INTERPOLATE_DISP] 
5762   
5763          # Write to temp folder. 
5764          result_dir_name = ds.tmpdir 
5765          result_folders = [model] 
5766          spin_id = ":61@N" 
5767   
5768          # Loop through all possible combinations of y_axis, x_axis and interpolation. 
5769          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+expfolder+sep+'check_graphs' 
5770   
5771          for result_folder in result_folders: 
5772              for y_axis in y_axis_types: 
5773                  for x_axis in x_axis_types: 
5774                      for interpolate in interpolate_types: 
5775                          # Determine file name: 
5776                          file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
5777   
5778                          # Make the file name. 
5779                          file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
5780   
5781                          # Write the curves. 
5782                          dir = result_dir_name+sep+result_folder 
5783                          print("Plotting combination of %s, %s, %s"%(y_axis, x_axis, interpolate)) 
5784                          self.interpreter.relax_disp.plot_disp_curves(dir=dir, y_axis=y_axis, x_axis=x_axis, interpolate=interpolate, force=True) 
5785   
5786                          # Get the file path. 
5787                          file_path = get_file_path(file_name, dir) 
5788   
5789                          # Test the plot file exists. 
5790                          print("Testing file access to graph: %s"%file_path) 
5791                          self.assert_(access(file_path, F_OK)) 
5792   
5793                          # Now open, and compare content, line by line. 
5794                          file_prod = open(file_path) 
5795                          lines_prod = file_prod.readlines() 
5796                          file_prod.close() 
5797   
5798                          # Define file to compare against. 
5799                          dir_comp = data_path+sep+result_folder 
5800                          file_path_comp = get_file_path(file_name, dir_comp) 
5801                          file_comp = open(file_path_comp) 
5802                          lines_comp = file_comp.readlines() 
5803                          file_comp.close() 
5804   
5805                          ## Assert number of lines is equal. 
5806                          self.assertEqual(len(lines_prod), len(lines_comp)) 
5807                          for j in range(len(lines_prod)): 
5808                              # Make the string test 
5809                              first_char = lines_prod[j][0] 
5810                              if first_char in ["@", "&"]: 
5811                                  self.assertEqual(lines_prod[j], lines_comp[j]) 
5812                              else: 
5813                                  # Split string in x, y, error. 
5814                                  # The error would change per run. 
5815                                  x_prod, y_prod, y_prod_err = lines_prod[j].split() 
5816                                  x_comp, y_comp, y_comp_err = lines_comp[j].split() 
5817                                  self.assertAlmostEqual(float(x_prod), float(x_comp)) 
5818                                  self.assertAlmostEqual(float(y_prod), float(y_comp)) 
5819                                  self.assertAlmostEqual(float(y_prod_err), float(y_comp_err)) 
5820   
5821   
5822 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_cr72(self): 
5823          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5824   
5825          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5826          """ 
5827   
5828          # Base data setup. 
5829          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='CR72', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5830   
5831          # Alias the spins. 
5832          res61L = cdp.mol[0].res[0].spin[0] 
5833   
5834          # The R20 keys. 
5835          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5836   
5837          # Set the initial parameter values. 
5838          res61L.r2 = {r20_key1: 8.0} 
5839          res61L.pA = 0.9 
5840          res61L.dw = 6.0 
5841          res61L.kex = 600.0 
5842   
5843          # Low precision optimisation. 
5844          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5845   
5846          # Printout. 
5847          print("\n\nOptimised parameters:\n") 
5848          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5849          print("%-20s %20.15g" % ("R2 (600 MHz)", res61L.r2[r20_key1])) 
5850          print("%-20s %20.15g" % ("pA", res61L.pA)) 
5851          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5852          print("%-20s %20.15g" % ("kex", res61L.kex)) 
5853          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5854   
5855          # Checks for residue :61. Calculated for 500 Monte Carlo simulations. 
5856          self.assertAlmostEqual(res61L.r2[r20_key1], 8.69277980194016, 4) 
5857          self.assertAlmostEqual(res61L.pA, 0.9943781590842946, 5) 
5858          self.assertAlmostEqual(res61L.dw, 6.389453131263374, 3) 
5859          self.assertAlmostEqual(res61L.kex, 609.262167216419, 0) 
5860          self.assertAlmostEqual(res61L.chi2, 65.99987828889657, 5) 
5861   
5862          # Test the conversion to k_AB from kex and pA. 
5863          self.assertEqual(res61L.k_AB, res61L.kex * (1.0 - res61L.pA)) 
5864   
5865          # Test the conversion to k_BA from kex and pA. 
5866          self.assertEqual(res61L.k_BA, res61L.kex * res61L.pA) 
5867   
5868   
5869 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_cr72_full(self): 
5870          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5871   
5872          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5873          """ 
5874   
5875          # Base data setup. 
5876          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='CR72 full', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5877   
5878          # Alias the spins. 
5879          res61L = cdp.mol[0].res[0].spin[0] 
5880   
5881          # The R20 keys. 
5882          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5883   
5884          # Set the initial parameter values. 
5885          res61L.r2a = {r20_key1: 8.0} 
5886          res61L.r2b = {r20_key1: 105.0} 
5887          res61L.pA = 0.9 
5888          res61L.dw = 6.0 
5889          res61L.kex = 500.0 
5890   
5891          # Low precision optimisation. 
5892          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5893   
5894          # Printout. 
5895          print("\n\nOptimised parameters:\n") 
5896          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5897          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5898          print("%-20s %20.15g" % ("R2B (600 MHz)", res61L.r2b[r20_key1])) 
5899          print("%-20s %20.15g" % ("pA", res61L.pA)) 
5900          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5901          print("%-20s %20.15g" % ("kex", res61L.kex)) 
5902          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5903   
5904          # Checks for residue :61. Calculated for 500 Monte Carlo simulations. 
5905          self.assertAlmostEqual(res61L.r2a[r20_key1], 8.044428899438309, 0) 
5906          self.assertAlmostEqual(res61L.r2b[r20_key1], 105.11894506392449, -2) 
5907          self.assertAlmostEqual(res61L.pA, 0.992066883657578, 2) 
5908          self.assertAlmostEqual(res61L.dw, 6.389453586338883, 3) 
5909          self.assertAlmostEqual(res61L.kex, 513.483608742063, -2) 
5910          self.assertAlmostEqual(res61L.chi2, 65.99987828890289, 5) 
5911   
5912   
5913 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_tsmfk01(self): 
5914          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5915   
5916          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5917   
5918          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl. The precise values are: 
5919   
5920            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5921            - 0.483 0.89623903 2.4503699912708878 
5922            - 0.545 1.1694838 
5923            - 0.545 1.1761503 
5924            - 0.622 1.294 
5925            - 0.669 1.5176493 
5926            - 0.722 1.6238791 
5927            - 0.813 1.9395758 
5928            - 1.011 2.3558415 10.547000429321157 
5929          """ 
5930   
5931          # Base data setup. 
5932          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='TSMFK01', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5933   
5934          # Alias the spins. 
5935          res61L = cdp.mol[0].res[0].spin[0] 
5936   
5937          # The R20 keys. 
5938          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5939   
5940          # Set the initial parameter values. 
5941          res61L.r2a = {r20_key1: 8.0} 
5942          res61L.dw = 6.5 
5943          res61L.k_AB = 2.5 
5944   
5945          # Low precision optimisation. 
5946          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5947   
5948          # Printout. 
5949          print("\n\nOptimised parameters:\n") 
5950          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5951          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5952          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5953          print("%-20s %20.15g" % ("k_AB", res61L.k_AB)) 
5954          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5955   
5956          # Checks for residue :61. Reference values from paper 
5957   
5958          self.assertAlmostEqual(res61L.k_AB, 2.45, 1) 
5959   
5960   
5961 -    def test_kteilum_fmpoulsen_makke_cpmg_data_101m_guhcl_to_tsmfk01(self): 
5962          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5963   
5964          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 1.01 M GuHCl (guanidine hydrochloride). 
5965   
5966          The comparison is to Figure 2, which is for dataset with 1 M GuHCl.  The reported results are expected to be in rad.s^-1.  Conversion into relax stored values is preferably. 
5967   
5968          Representative 15N CPMG relaxation dispersion curve measured on the cross peaks from residue L61 in folded ACBP at pH 5.3, 1 M GuHCl, and 40C: 
5969   
5970            1. The dotted line represents a residue-specific fit of all parameters in Eq. 1: 
5971              - k_AB = 11.3 +/- 0.7 s^-1, 
5972              - dw = (2.45 +/- 0.09) * 10^3 s^-1, 
5973              - R2 = 8.0 +/- 0.5 s^-1. 
5974   
5975            2. The solid line represents a global fit of k_AB to all protein residues and a residue-specific fit of dw and R2.: 
5976              - k_AB = 10.55 +/- 0.08 s^-1, 
5977              - dw = (2.44 +/- 0.08) * 10^3 s^-1, 
5978              - R2 = 8.4 +/- 0.3 s^-1. 
5979   
5980          Conversion of paper results to relax results is performed by: 
5981   
5982            - dw(ppm) = dw(rad.s^-1) * 10^6 * 1/(2*pi) * (gyro1H/(gyro15N*spectrometer_freq)) = 2.45E3 * 1E6 / (2 * math.pi) * (26.7522212E7/(-2.7126E7 * 599.8908622E6)) = -6.41 ppm. 
5983   
5984          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl.  The precise values are: 
5985   
5986            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5987            - 0.483 0.89623903 2.4503699912708878 
5988            - 0.545 1.1694838 
5989            - 0.545 1.1761503 
5990            - 0.622 1.294 
5991            - 0.669 1.5176493 
5992            - 0.722 1.6238791 
5993            - 0.813 1.9395758 
5994            - 1.011 2.3558415 10.547000429321157 
5995          """ 
5996   
5997          # Base data setup. 
5998          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='TSMFK01', expfolder="acbp_cpmg_disp_101MGuHCl_40C_041223") 
5999   
6000          # Alias the spins. 
6001          res61L = cdp.mol[0].res[0].spin[0] 
6002   
6003          # The R20 keys. 
6004          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086270e6) 
6005   
6006          # Set the initial parameter values. 
6007          res61L.r2a = {r20_key1: 8.0} 
6008          res61L.dw = 6.5 
6009          res61L.k_AB = 11.0 
6010   
6011          # Low precision optimisation. 
6012          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
6013   
6014          # Printout. 
6015          print("\n\nOptimised parameters:\n") 
6016          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
6017          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
6018          print("%-20s %20.15g" % ("dw", res61L.dw)) 
6019          print("%-20s %20.15g" % ("k_AB", res61L.k_AB)) 
6020          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
6021   
6022          # Checks for residue :61. Reference values from paper 
6023   
6024          self.assertAlmostEqual(res61L.r2a[r20_key1], 8.4, 0) 
6025          self.assertAlmostEqual(res61L.dw, 6.41, 0) 
6026          self.assertAlmostEqual(res61L.k_AB, 10.55, 0) 
6027   
6028   
6029 -    def test_lm63_3site_synthetic(self): 
6030          """Test the 'LM63 3-site' dispersion model using the pure noise-free synthetic data.""" 
6031   
6032          # The path to the data files. 
6033          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'lm63_3site' 
6034   
6035          # Load the state file. 
6036          self.interpreter.reset() 
6037          self.interpreter.state.load(data_path+sep+'r2eff_values') 
6038   
6039          # A new data pipe. 
6040          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to='LM63 3-site', bundle_to='relax_disp') 
6041          self.interpreter.pipe.switch(pipe_name='LM63 3-site') 
6042   
6043          # Set up the model data. 
6044          self.interpreter.relax_disp.select_model(model='LM63 3-site') 
6045          self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to='LM63 3-site', param='r2eff') 
6046          self.interpreter.spin.isotope('15N') 
6047   
6048          # Alias the spins. 
6049          spin1 = return_spin(":1") 
6050          spin2 = return_spin(":2") 
6051   
6052          # The R20 keys. 
6053          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
6054          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
6055   
6056          # Manually set the parameter values. 
6057          spin1.r2 = {r20_key1: 12.0, r20_key2: 12.0} 
6058          spin1.phi_ex_B = 0.1 
6059          spin1.phi_ex_C = 0.5 
6060          spin1.kB = 1500.0 
6061          spin1.kC = 2500.0 
6062          spin2.r2 = {r20_key1: 15.0, r20_key2: 15.0} 
6063          spin2.phi_ex_B = 0.1 
6064          spin2.phi_ex_C = 0.5 
6065          spin2.kB = 1500.0 
6066          spin2.kC = 2500.0 
6067   
6068          # Low precision optimisation. 
6069          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
6070   
6071          # Monte Carlo simulations. 
6072          self.interpreter.monte_carlo.setup(number=3) 
6073          self.interpreter.monte_carlo.create_data(method='back_calc') 
6074          self.interpreter.monte_carlo.initial_values() 
6075          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-2, grad_tol=None, max_iter=10, constraints=True, scaling=True, verbosity=1) 
6076          self.interpreter.monte_carlo.error_analysis() 
6077   
6078          # Save the results. 
6079          self.interpreter.results.write(file='devnull', compress_type=1, force=True) 
6080   
6081          # The model checks. 
6082          print("\n\nOptimised parameters:\n") 
6083          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
6084          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
6085          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
6086          print("%-20s %20.15g %20.15g" % ("phi_ex_B", spin1.phi_ex_B, spin2.phi_ex_B)) 
6087          print("%-20s %20.15g %20.15g" % ("phi_ex_C", spin1.phi_ex_C, spin2.phi_ex_C)) 
6088          print("%-20s %20.15g %20.15g" % ("kB", spin1.kB, spin2.kB)) 
6089          print("%-20s %20.15g %20.15g" % ("kC", spin1.kC, spin2.kC)) 
6090          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
6091          self.assertAlmostEqual(spin1.r2[r20_key1], 12.0, 2) 
6092          self.assertAlmostEqual(spin1.r2[r20_key2], 12.0, 2) 
6093          self.assertAlmostEqual(spin1.phi_ex_B, 0.1, 3) 
6094          self.assertAlmostEqual(spin1.phi_ex_C, 0.5, 3) 
6095          self.assertAlmostEqual(spin1.kB/1000, 1500.0/1000, 3) 
6096          self.assertAlmostEqual(spin1.kC/1000, 2500.0/1000, 3) 
6097          self.assertAlmostEqual(spin1.chi2, 0.0, 3) 
6098          self.assertAlmostEqual(spin2.r2[r20_key1], 15.0, 3) 
6099          self.assertAlmostEqual(spin2.r2[r20_key2], 15.0, 3) 
6100          self.assertAlmostEqual(spin1.phi_ex_B, 0.1, 3) 
6101          self.assertAlmostEqual(spin1.phi_ex_C, 0.5, 3) 
6102          self.assertAlmostEqual(spin1.kB/1000, 1500.0/1000, 3) 
6103          self.assertAlmostEqual(spin1.kC/1000, 2500.0/1000, 3) 
6104          self.assertAlmostEqual(spin2.chi2, 0.0, 3) 
6105   
6106   
6107 -    def test_m61_data_to_m61(self): 
6108          """Test the relaxation dispersion 'M61' model curve fitting to fixed time synthetic data.""" 
6109   
6110          # Fixed time variable. 
6111          ds.fixed = True 
6112   
6113          # Execute the script. 
6114          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61.py') 
6115   
6116          # The original parameters. 
6117          i0 = [100000.0, 20000.0] 
6118          r1rho_prime = [2.25, 24.0] 
6119          pA = 0.7 
6120          kex = 1000.0 
6121          delta_omega = [1.0, 2.0] 
6122          keys = ['r1rho_800.00000000_0.000_1000.000', 'r1rho_800.00000000_0.000_1500.000', 'r1rho_800.00000000_0.000_2000.000', 'r1rho_800.00000000_0.000_2500.000', 'r1rho_800.00000000_0.000_3000.000', 'r1rho_800.00000000_0.000_3500.000', 'r1rho_800.00000000_0.000_4000.000', 'r1rho_800.00000000_0.000_4500.000', 'r1rho_800.00000000_0.000_5000.000', 'r1rho_800.00000000_0.000_5500.000', 'r1rho_800.00000000_0.000_6000.000'] 
6123          phi_ex = [] 
6124          for i in range(2): 
6125              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
6126          rates = [[3.59768160399, 2.85730469783, 2.59328084312, 2.47019857325, 2.40310451058, 2.36256876552, 2.33622716364, 2.31815271355, 2.30521680479, 2.29564174079, 2.28835686631], [29.390726416, 26.4292187913, 25.3731233725, 24.880794293, 24.6124180423, 24.4502750621, 24.3449086546, 24.2726108542, 24.2208672192, 24.1825669632, 24.1534274652]] 
6127   
6128          # Switch to the 'R2eff' model data pipe, then check for each spin. 
6129          self.interpreter.pipe.switch('R2eff - relax_disp') 
6130          spin_index = 0 
6131          for spin, spin_id in spin_loop(return_id=True): 
6132              # Printout. 
6133              print("\nSpin %s." % spin_id) 
6134   
6135              # Check the fitted parameters. 
6136              for i in range(len(keys)): 
6137                  self.assertAlmostEqual(spin.r2eff[keys[i]]/10.0, rates[spin_index][i]/10.0, 2) 
6138   
6139              # Increment the spin index. 
6140              spin_index += 1 
6141   
6142          # The R20 keys. 
6143          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6144   
6145          # Switch to the 'M61' model data pipe, then check for each spin. 
6146          self.interpreter.pipe.switch('M61 - relax_disp') 
6147          spin_index = 0 
6148          for spin, spin_id in spin_loop(return_id=True): 
6149              # Printout. 
6150              print("\nSpin %s." % spin_id) 
6151   
6152              # Check the fitted parameters. 
6153              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6154              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
6155              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6156   
6157              # Increment the spin index. 
6158              spin_index += 1 
6159   
6160   
6161 -    def test_m61_exp_data_to_m61(self): 
6162          """Test the relaxation dispersion 'M61' model curve fitting to the full exponential synthetic data.""" 
6163   
6164          # Fixed time variable. 
6165          ds.fixed = False 
6166   
6167          # Single spin optimisation. 
6168          ds.single = True 
6169   
6170          # Execute the script. 
6171          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61.py') 
6172   
6173          # The original parameters. 
6174          i0 = [100000.0, 20000.0] 
6175          r1rho_prime = [2.25, 24.0] 
6176          pA = 0.7 
6177          kex = 1000.0 
6178          delta_omega = [1.0, 2.0] 
6179          keys = ['r1rho_800.00000000_0.000_1000.000', 'r1rho_800.00000000_0.000_1500.000', 'r1rho_800.00000000_0.000_2000.000', 'r1rho_800.00000000_0.000_2500.000', 'r1rho_800.00000000_0.000_3000.000', 'r1rho_800.00000000_0.000_3500.000', 'r1rho_800.00000000_0.000_4000.000', 'r1rho_800.00000000_0.000_4500.000', 'r1rho_800.00000000_0.000_5000.000', 'r1rho_800.00000000_0.000_5500.000', 'r1rho_800.00000000_0.000_6000.000'] 
6180          phi_ex = [] 
6181          for i in range(2): 
6182              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
6183          rates = [[3.59768160399, 2.85730469783, 2.59328084312, 2.47019857325, 2.40310451058, 2.36256876552, 2.33622716364, 2.31815271355, 2.30521680479, 2.29564174079, 2.28835686631], [29.390726416, 26.4292187913, 25.3731233725, 24.880794293, 24.6124180423, 24.4502750621, 24.3449086546, 24.2726108542, 24.2208672192, 24.1825669632, 24.1534274652]] 
6184   
6185          # Switch to the 'R2eff' model data pipe, then check for each spin. 
6186          self.interpreter.pipe.switch('R2eff - relax_disp') 
6187          spin_index = 0 
6188          for spin, spin_id in spin_loop(return_id=True): 
6189              # Printout. 
6190              print("\nSpin %s." % spin_id) 
6191   
6192              # Check the fitted parameters. 
6193              for i in range(len(keys)): 
6194                  self.assertAlmostEqual(spin.r2eff[keys[i]]/10.0, rates[spin_index][i]/10.0, 2) 
6195   
6196              # Increment the spin index. 
6197              spin_index += 1 
6198   
6199          # The R20 keys. 
6200          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6201   
6202          # Switch to the 'M61' model data pipe, then check for each spin. 
6203          self.interpreter.pipe.switch('M61 - relax_disp') 
6204          spin_index = 0 
6205          for spin, spin_id in spin_loop(return_id=True): 
6206              # Printout. 
6207              print("\nSpin %s." % spin_id) 
6208   
6209              # Check the fitted parameters. 
6210              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6211              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
6212              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6213   
6214              # Increment the spin index. 
6215              spin_index += 1 
6216   
6217   
6218 -    def test_m61b_data_to_m61b(self): 
6219          """Test the relaxation dispersion 'M61 skew' model curve fitting to fixed time synthetic data.""" 
6220   
6221          # Execute the script. 
6222          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61b.py') 
6223   
6224          # The original parameters. 
6225          i0 = [100000.0, 20000.0] 
6226          r1rho_prime = [10.0, 24.0] 
6227          pA = 0.95 
6228          kex = 2000.0 
6229          delta_omega = [1.0, 2.0] 
6230   
6231          # The R20 keys. 
6232          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6233   
6234          # Switch to the 'M61 skew' model data pipe, then check for each spin. 
6235          self.interpreter.pipe.switch("%s - relax_disp" % MODEL_M61B) 
6236          spin_index = 0 
6237          for spin, spin_id in spin_loop(return_id=True): 
6238              # Printout. 
6239              print("\nSpin %s." % spin_id) 
6240   
6241              # Check the fitted parameters. 
6242              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6243              self.assertAlmostEqual(spin.pA, pA, 2) 
6244              self.assertAlmostEqual(spin.dw, dw[spin_index], 2) 
6245              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6246   
6247              # Increment the spin index. 
6248              spin_index += 1 
6249   
6250   
6251 -    def test_model_nesting_and_param(self): 
6252          """Test that all models which can nest, have all their parameters converted.""" 
6253   
6254          # Set the experiment type. 
6255          cdp.exp_type_list = EXP_TYPE_LIST 
6256   
6257          # Get info for all models. 
6258          all_models_info = models_info(models=MODEL_LIST_FULL) 
6259   
6260          # Loop over all models. 
6261          print("Printing the listed of nested models for each model.") 
6262          print("#########################################") 
6263          for model_info in all_models_info: 
6264              print("%s"%model_info.model), 
6265              print("<-"), 
6266              nest_list = model_info.nest_list 
6267              if nest_list == None: 
6268                  nest_list = ["None"] 
6269              print(', '.join(map(str, nest_list))) 
6270   
6271              # Skip if there is no model to nest from. 
6272              if nest_list == ["None"]: 
6273                  continue 
6274   
6275              # Assign params to variable. 
6276              model_params = model_info.params 
6277   
6278              # Now loop over the nested models. 
6279              for nested_model in nest_list: 
6280                  # Get the params for the nested model. 
6281                  nested_model_params = MODEL_PARAMS[nested_model] 
6282   
6283                  # Get the dictionary of parameter conversion. 
6284                  par_dic = nesting_param(model_params=model_params, nested_model_params=nested_model_params) 
6285   
6286                  # Test the number of elements in the dictionary. 
6287                  self.assertEqual(len(par_dic), len(model_params)) 
6288   
6289                  # Loop over dictionary. 
6290                  for param in par_dic: 
6291                          if param != par_dic[param]: 
6292                              print("Model:'%s', Nested model:'%s', Copying '%s' to '%s'." % (model_info.model, nested_model, par_dic[param], param)) 
6293                          self.assertNotEqual(par_dic[param], None) 
6294   
6295   
6296 -    def test_ns_mmq_3site(self): 
6297          """Compare the 'NS MMQ 3-site' dispersion model to synthetic data from cpmg_fit.""" 
6298   
6299          # Execute the script. 
6300          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_mmq_3site.py') 
6301   
6302          # Check the chi-squared value. 
6303          self.assertAlmostEqual(cdp.mol[0].res[0].spin[1].chi2, 0.0, 3) 
6304   
6305   
6306 -    def test_ns_mmq_3site_linear(self): 
6307          """Compare the 'NS MMQ 3-site linear' dispersion model to synthetic data from cpmg_fit.""" 
6308   
6309          # Execute the script. 
6310          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_mmq_3site_linear.py') 
6311   
6312          # Check the chi-squared value. 
6313          self.assertAlmostEqual(cdp.mol[0].res[0].spin[1].chi2, 0.0, 3) 
6314   
6315   
6316 -    def test_ns_r1rho_3site(self): 
6317          """Compare the 'NS R1rho 3-site' dispersion model to synthetic data from cpmg_fit.""" 
6318   
6319          # Execute the script. 
6320          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_r1rho_3site.py') 
6321   
6322          # Check the chi-squared value. 
6323          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].chi2, 136.13141468674999, 3) 
6324   
6325   
6326 -    def test_ns_r1rho_3site_linear(self): 
6327          """Compare the 'NS R1rho 3-site linear' dispersion model to synthetic data from cpmg_fit.""" 
6328   
6329          # Execute the script. 
6330          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_r1rho_3site_linear.py') 
6331   
6332          # Check the chi-squared value. 
6333          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].chi2, 0.030959849811015544, 3) 
6334   
6335   
6336 -    def test_paul_schanda_nov_2015(self): 
6337          """This test truncated private data which was provided by Paul Schanda.  This systemtest uncovers some unfortunate problems when 
6338          running an analysis and reading points by the R2eff method. 
6339          """ 
6340   
6341          # Assign 
6342          outdir = ds.tmpdir 
6343   
6344          # Execute the setup and creation of files. 
6345          self.setup_paul_schanda_nov_2015(outdir=outdir) 
6346   
6347          # Minimum: Just read the sequence data, but this misses a lot of information. 
6348          self.interpreter.sequence.read(file='residues.txt', res_num_col=1, dir=outdir) 
6349   
6350          # Open the settings file. 
6351          set_file = open(outdir+sep+"exp_settings.txt") 
6352          set_file_lines = set_file.readlines() 
6353   
6354          # Now load the data. 
6355          for line in set_file_lines: 
6356              if "#" in line[0]: 
6357                  continue 
6358   
6359              # Get data 
6360              field, RF_field_strength_kHz, f_name = line.split() 
6361   
6362              # Assign data 
6363              spec_id = f_name 
6364              self.interpreter.relax_disp.exp_type(spectrum_id=spec_id, exp_type='R1rho') 
6365   
6366              # Set the spectrometer frequency 
6367              self.interpreter.spectrometer.frequency(id=spec_id, frq=float(field), units='MHz') 
6368   
6369              # Is in kHz, som convert to Hz 
6370              disp_frq = float(RF_field_strength_kHz)*1000 
6371   
6372              # Set The spin-lock field strength, nu1, in Hz 
6373              self.interpreter.relax_disp.spin_lock_field(spectrum_id=spec_id, field=disp_frq) 
6374   
6375              # Read the R2eff data 
6376              self.interpreter.relax_disp.r2eff_read(id=spec_id, file=f_name, dir=None, disp_frq=disp_frq, res_num_col=1, data_col=2, error_col=3) 
6377   
6378              # Is this necessary? The time, in seconds, of the relaxation period. 
6379              #self.interpreter.relax_disp.relax_time(spectrum_id=spec_id, time=time_sl) 
6380   
6381   
6382          # Check that the number of R2eff points is correct after dropping 1 datapoint for spin 51. 
6383          r2eff_points = [] 
6384          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
6385              # Loop over the R2eff points 
6386              for key in cur_spin.r2eff: 
6387                  value = cur_spin.r2eff[key] 
6388                  err = cur_spin.r2eff_err[key] 
6389                  r2eff_points.append(value) 
6390   
6391                  # Test that values and errors are not nan. 
6392                  self.assert_(not isnan(value)) 
6393                  self.assert_(not isnan(err)) 
6394   
6395   
6396          # Test the number of r2eff points. One is subtracted, due to one of the error values are "nan" in spin 51. 
6397          self.assertEqual(len(r2eff_points), 2*(10+19)-1) 
6398   
6399          # Test stored value in the pipe. 
6400          self.assertEqual(len(cdp.mol), 1) 
6401          self.assertEqual(cdp.mol[0].name, None) 
6402          self.assertEqual(len(cdp.mol[0].res), 2) 
6403   
6404          self.assertEqual(cdp.spectrometer_frq_count, 2) 
6405          print cdp.spectrometer_frq_list 
6406          self.assertEqual(cdp.spectrometer_frq_list, [600000000.0, 950000000.0]) 
6407          self.assertEqual(cdp.exp_type_list, ['R1rho']) 
6408   
6409          # Test the number of frequencies. 
6410          count_600 = 0 
6411          count_950 = 0 
6412          for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
6413              if frq == cdp.spectrometer_frq_list[0]: 
6414                  count_600 += 1 
6415              elif frq == cdp.spectrometer_frq_list[1]: 
6416                  count_950 += 1 
6417   
6418          # Assert the number of points 
6419          self.assertEqual(count_600, 10) 
6420          self.assertEqual(count_950, 19) 
6421   
6422          # Name the isotope for field strength scaling. 
6423          self.interpreter.spin.isotope(isotope='15N') 
6424   
6425          # Now test that the plotting can be performed of just the raw data. 
6426          self.assertRaises(RelaxError, self.interpreter.relax_disp.plot_disp_curves, dir=outdir, y_axis='r2_eff', x_axis='disp', num_points=1000, extend_hz=500.0, extend_ppm=500.0, interpolate='disp', force=True) 
6427          self.interpreter.relax_disp.select_model(model=MODEL_R2EFF) 
6428          self.interpreter.relax_disp.plot_disp_curves(dir=outdir, y_axis='r2_eff', x_axis='disp', num_points=1000, extend_hz=500.0, extend_ppm=500.0, interpolate='disp', force=True) 
6429   
6430   
6431          # Number of grid search increments.  If set to None, then the grid search will be turned off and the default parameter values will be used instead. 
6432          #GRID_INC = None 
6433          GRID_INC = 21 
6434          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
6435          MC_NUM = 3 
6436          # Model selection technique. 
6437          MODSEL = 'AIC' 
6438          # Which models to analyse ? 
6439          MODELS = [MODEL_NOREX, MODEL_M61] 
6440          # Fit, instead of read. Off for On-resonance. 
6441          r1_fit = False 
6442          # Set the initial guess from the minimum R2eff point 
6443          set_grid_r20=True 
6444   
6445          # Execute the auto-analysis (fast). 
6446          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
6447          OPT_FUNC_TOL = 1e-1 
6448          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
6449          OPT_MAX_ITERATIONS = 1000 
6450          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
6451   
6452          # Go 
6453          relax_disp.Relax_disp(pipe_name="relax_disp", pipe_bundle="relax_disp", results_dir=outdir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, exp_mc_sim_num=None, modsel=MODSEL,  pre_run_dir=None, optimise_r2eff=False, insignificance=0.0, numeric_only=False, mc_sim_all_models=False, eliminate=True, set_grid_r20=set_grid_r20, r1_fit=r1_fit) 
6454   
6455          # Now simulate that all spins are first deselected, and then selected. 
6456          self.interpreter.deselect.all() 
6457          sel_ids = [ 
6458          ":12", 
6459          ":51", 
6460          ] 
6461          for sel_spin in sel_ids: 
6462              print("Selecting spin %s"%sel_spin) 
6463              self.interpreter.select.spin(spin_id=sel_spin, change_all=False) 
6464   
6465          # Inspect which residues should be analysed together for a clustered/global fit. 
6466          cluster_ids = sel_ids 
6467   
6468          # Cluster spins 
6469          for curspin in cluster_ids: 
6470              print("Adding spin %s to cluster"%curspin) 
6471              self.interpreter.relax_disp.cluster('model_cluster', curspin) 
6472   
6473          # Show the pipe 
6474          print("\nPrinting all the available pipes.") 
6475          self.interpreter.pipe.display() 
6476   
6477          # Get the selected models 
6478          print("\nChecking which model is stored per spin.") 
6479          for curspin, mol_name, res_num, res_name, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
6480              print("For spin_id '%s the model is '%s''"%(spin_id, curspin.model)) 
6481   
6482          # Copy pipe and switch to it. 
6483          self.interpreter.pipe.copy(pipe_from="final - relax_disp", pipe_to="relax_disp_cluster", bundle_to="relax_disp_cluster") 
6484          self.interpreter.pipe.switch(pipe_name="relax_disp_cluster") 
6485          self.interpreter.pipe.display() 
6486   
6487          # Go again with clustered spins. 
6488          relax_disp.Relax_disp(pipe_name="relax_disp_cluster", pipe_bundle="relax_disp_cluster", results_dir=outdir+sep+"cluster", models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, exp_mc_sim_num=None, modsel=MODSEL,  pre_run_dir=None, optimise_r2eff=False, insignificance=0.0, numeric_only=False, mc_sim_all_models=False, eliminate=True, set_grid_r20=set_grid_r20, r1_fit=r1_fit) 
6489   
6490          # Get the clustered fitted values 
6491          print("\nChecking which value is stored per spin.") 
6492          kex = None 
6493          for curspin, mol_name, res_num, res_name, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
6494              if kex == None: 
6495                  kex = curspin.kex 
6496              self.assertEqual(curspin.kex, kex) 
6497              print("For spin_id %s the kex is %.3f"%(spin_id, kex)) 
6498   
6499   
6500 -    def test_repeat_cpmg(self): 
6501          """Test the protocol for repeated dispersion analysis. The class: relax_disp_repeat_cpmg. 
6502   
6503          U{task #7826<https://gna.org/task/index.php?7826>}. Write an python class for the repeated analysis of dispersion data. 
6504          """ 
6505   
6506          # Reset. 
6507          self.interpreter.reset() 
6508   
6509          # Define base path to files. 
6510          base_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1' 
6511   
6512          # Setup dictionary with settings. 
6513          sdic = {} 
6514   
6515          # Spectrometer frqs in list. 
6516          sfrq_1 = 499.86214 
6517          sfrq_2 = 599.8908587 
6518          sfrqs = [sfrq_1, sfrq_2] 
6519   
6520          # Store in dictionary. 
6521          sdic['sfrqs'] = sfrqs 
6522   
6523          # Store unit for frq. 
6524          sdic['sfrq_unit'] = 'MHz' 
6525   
6526          # Store exp_type 
6527          sdic['exp_type'] = 'SQ CPMG' 
6528   
6529          # Store spin isotope 
6530          sdic['isotope'] = '15N' 
6531   
6532          # How intensity was measured. 
6533          sdic['int_method'] = 'height' 
6534   
6535          # Define the time for result directory. 
6536          sdic['time'] = '2014_09' 
6537   
6538          # Initialize frq dics. 
6539          for frq in sfrqs: 
6540              key = DIC_KEY_FORMAT % (frq) 
6541              sdic[key] = {} 
6542   
6543          # Set keys. 
6544          e_1 = DIC_KEY_FORMAT % (sfrq_1) 
6545          e_2 = DIC_KEY_FORMAT % (sfrq_2) 
6546   
6547          # Store time T2. 
6548          sdic[e_1]['time_T2'] = 0.04 
6549          sdic[e_2]['time_T2'] = 0.06 
6550   
6551          # Set ncyc. 
6552          ncyc_1 = array([20, 0, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28, 0]) 
6553          ncyc_2 = array([28, 0, 4, 32, 60, 2, 10, 16, 8, 20, 52, 18, 40, 6, 12, 0, 24, 14, 22]) 
6554   
6555          # Calculate the cpmg_frq and store. 
6556          sdic[e_1]['cpmg_frqs'] = ncyc_1 / sdic[e_1]['time_T2'] 
6557          sdic[e_2]['cpmg_frqs'] = ncyc_2 / sdic[e_2]['time_T2'] 
6558   
6559          # Define peak lists. 
6560          peaks_folder_1 = base_path +sep+ 'cpmg_disp_sod1d90a_060518' +sep+ 'cpmg_disp_sod1d90a_060518_normal.fid' +sep+ 'analysis_FT' +sep+ 'ser_files' 
6561          peaks_folder_2 = base_path +sep+ 'cpmg_disp_sod1d90a_060521' +sep+ 'cpmg_disp_sod1d90a_060521_normal.fid' +sep+ 'analysis_FT' +sep+ 'ser_files'  
6562          sdic[e_1]['peaks_folder'] = peaks_folder_1 
6563          sdic[e_2]['peaks_folder'] = peaks_folder_2 
6564   
6565          # Define folder to all rmsd files. 
6566          rmsd_folder_1 = base_path +sep+ 'cpmg_disp_sod1d90a_060518' +sep+ 'cpmg_disp_sod1d90a_060518_normal.fid' +sep+ 'ft2_data' 
6567          rmsd_folder_2 = base_path +sep+ 'cpmg_disp_sod1d90a_060521' +sep+ 'cpmg_disp_sod1d90a_060521_normal.fid' +sep+ 'ft2_data' 
6568          sdic[e_1]['rmsd_folder'] = rmsd_folder_1  
6569          sdic[e_2]['rmsd_folder'] = rmsd_folder_2 
6570   
6571          # Define temporary folder. 
6572          sdic['results_dir'] = self.tmpdir 
6573   
6574          # Setup class with data. 
6575          RDR =  Relax_disp_rep(sdic) 
6576   
6577          # Setup base information. 
6578          RDR.set_base_cpmg(method='FT', glob_ini=128) 
6579   
6580          methods = ['FT', 'MDD'] 
6581          #methods = ['FT'] 
6582   
6583          # Set the intensity. 
6584          #RDR.set_int(methods=methods, list_glob_ini=[128, 126], set_rmsd=False, set_rep=True) 
6585          #RDR.set_int(methods=methods, list_glob_ini=[128, 126], set_rmsd=True, set_rep=False) 
6586   
6587          # Try plot some intensity correlations. 
6588          if True: 
6589              selection = None 
6590   
6591              # Now make a spin selection. 
6592              int_ft_sel = RDR.col_int(method='FT', list_glob_ini=[128, 126], selection=selection) 
6593   
6594              # For mdd 
6595              int_mdd_sel = RDR.col_int(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6596   
6597              # Plot correlation of intensity 
6598              fig1 = [[int_ft_sel, int_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6599              fig2 = [[int_ft_sel, int_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6600              corr_data = [fig1, fig2] 
6601   
6602              write_stats = True 
6603              RDR.plot_int_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6604   
6605              # Open stat file. 
6606              if write_stats: 
6607                  for i, corr_data_i in enumerate(corr_data): 
6608                      data, methods, glob_inis = corr_data[i] 
6609                      data_x, data_y = data 
6610                      method_x, method_y = methods 
6611                      glob_ini_x, glob_ini_y = glob_inis 
6612                      x = data_x[str(glob_ini_x)]['peak_intensity_arr'] 
6613                      np = len(x) 
6614   
6615                      file_name_ini = 'int_corr_%s_%s_%s_%s_NP_%i' % (method_x, glob_ini_x, method_y, glob_ini_y, np) 
6616   
6617                      if selection == None: 
6618                          file_name = file_name_ini + '_all.txt' 
6619                      else: 
6620                          file_name = file_name_ini + '_sel.txt' 
6621                      path = RDR.results_dir 
6622                      data = extract_data(file=file_name, dir=path) 
6623   
6624                      # Loop over the lines. 
6625                      for i, data_i in enumerate(data): 
6626                          print(i, data_i) 
6627   
6628   
6629          # Try plot some intensity statistics. 
6630          if True: 
6631              # Collect r2eff values. 
6632              selections = [None, ':2,3'] 
6633              for selection in selections: 
6634                  int_ft_sel = RDR.col_int(method='FT', list_glob_ini=[128], selection=selection) 
6635                  int_mdd_sel = RDR.col_int(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6636   
6637                  # Get R2eff stats. 
6638                  int_stat_dic = RDR.get_int_stat_dic(list_int_dics=[int_ft_sel, int_mdd_sel], list_glob_ini=[128, 126]) 
6639   
6640                  ## Plot R2eff stats 
6641                  write_stats = True 
6642                  RDR.plot_int_stat(int_stat_dic=int_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126], show=False, write_stats=write_stats) 
6643   
6644                  # Open stat file. 
6645                  if write_stats: 
6646                      if selection == None: 
6647                          file_name = 'int_stat_all.txt' 
6648                      else: 
6649                          file_name = 'int_stat_sel.txt' 
6650                      path = RDR.results_dir 
6651                      data = extract_data(file=file_name, dir=path) 
6652   
6653                      # Loop over the lines. 
6654                      for i, data_i in enumerate(data): 
6655                          print(i, data_i) 
6656   
6657   
6658          # Try write some R2eff correlations. 
6659          if True: 
6660              selection = None 
6661              # Collect r2eff values. 
6662              r2eff_ft_all = RDR.col_r2eff(method='FT', list_glob_ini=[128, 126, 6], selection=selection) 
6663   
6664              # For all spins, mdd 
6665              r2eff_mdd_all = RDR.col_r2eff(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6666   
6667              # Plot correlation of intensity 
6668              fig1 = [[r2eff_ft_all, r2eff_mdd_all], ['FT', 'MDD'], [128, 128]] 
6669              fig2 = [[r2eff_ft_all, r2eff_mdd_all], ['FT', 'MDD'], [128, 126]] 
6670              corr_data = [fig1, fig2] 
6671   
6672              write_stats = True 
6673              RDR.plot_r2eff_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6674   
6675              # Open stat file. 
6676              if write_stats: 
6677                  for i, corr_data_i in enumerate(corr_data): 
6678                      data, methods, glob_inis = corr_data[i] 
6679                      data_x, data_y = data 
6680                      method_x, method_y = methods 
6681                      glob_ini_x, glob_ini_y = glob_inis 
6682                      x = data_x[str(glob_ini_x)]['r2eff_arr'] 
6683                      np = len(x) 
6684   
6685                      file_name_ini = 'r2eff_corr_%s_%s_%s_%s_NP_%i' % (method_x, glob_ini_x, method_y, glob_ini_y, np) 
6686   
6687                      if selection == None: 
6688                          file_name = file_name_ini + '_all.txt' 
6689                      else: 
6690                          file_name = file_name_ini + '_sel.txt' 
6691                      path = RDR.results_dir 
6692                      data = extract_data(file=file_name, dir=path) 
6693   
6694                      # Loop over the lines. 
6695                      for i, data_i in enumerate(data): 
6696                          print(i, data_i) 
6697   
6698   
6699          # Try plot some R2eff statistics. 
6700          if True: 
6701              # Collect r2eff values. 
6702              selections = [None, ':2,3'] 
6703              for selection in selections: 
6704                  r2eff_ft_sel = RDR.col_r2eff(method='FT', list_glob_ini=[128, 126, 6], selection=selection) 
6705                  r2eff_mdd_sel = RDR.col_r2eff(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6706   
6707                  # Get R2eff stats. 
6708                  r2eff_stat_dic = RDR.get_r2eff_stat_dic(list_r2eff_dics=[r2eff_ft_sel, r2eff_mdd_sel], list_glob_ini=[128, 126]) 
6709   
6710                  ## Plot R2eff stats 
6711                  write_stats = True 
6712                  RDR.plot_r2eff_stat(r2eff_stat_dic=r2eff_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6713   
6714                  # Open stat file. 
6715                  if write_stats: 
6716                      if selection == None: 
6717                          file_name = 'r2eff_stat_all.txt' 
6718                      else: 
6719                          file_name = 'r2eff_stat_sel.txt' 
6720                      path = RDR.results_dir 
6721                      data = extract_data(file=file_name, dir=path) 
6722   
6723                      # Loop over the lines. 
6724                      for i, data_i in enumerate(data): 
6725                          print(i, data_i) 
6726   
6727   
6728          # Do minimisation individual. 
6729          if True: 
6730              methods = ['FT', 'MDD'] 
6731              # Now calculate R2eff. 
6732              RDR.calc_r2eff(methods=methods, list_glob_ini=[128, 126]) 
6733   
6734              min_methods = [['FT'], ['MDD']] 
6735              min_list_glob_ini = [[128], list(range(126, 130, 2))[::-1]] 
6736   
6737              #min_methods = [['FT']] 
6738              #min_list_glob_ini = [[128]] 
6739              #selection = ':2,3' 
6740              selection = None 
6741   
6742              for i, methods in enumerate(min_methods): 
6743                  list_glob_ini = min_list_glob_ini[i] 
6744   
6745                  if True: 
6746                      # First get data. 
6747                      if True: 
6748                          # First load all data. 
6749                          RDR.calc_r2eff(methods=methods, list_glob_ini=list_glob_ini) 
6750   
6751                      # Then set R20 
6752                      if True: 
6753                          # Set R20 from min R2eff in preparation for Grid search. 
6754                          RDR.r20_from_min_r2eff(methods=methods, model=MODEL_CR72, model_from=MODEL_R2EFF, analysis='grid_setup_ind', analysis_from='int', list_glob_ini=list_glob_ini, force=True) 
6755   
6756                      # Check and print parameters. 
6757                      if True: 
6758                          # Print for pipe name 
6759                          method = methods[0] 
6760                          glob_ini = list_glob_ini[0] 
6761   
6762                          test_pipe_name = RDR.name_pipe(method=method, model=MODEL_CR72, analysis='grid_setup_ind', glob_ini=glob_ini) 
6763                          RDR.spin_display_params(pipe_name=test_pipe_name) 
6764   
6765                      # Then Grid search. 
6766                      if True: 
6767                          # Do Grid search. 
6768                          RDR.minimise_grid_search(inc=4, verbosity=1, methods=methods, model=MODEL_CR72, analysis='grid_setup_ind', list_glob_ini=list_glob_ini, force=True) 
6769   
6770                  # Then Minimise. 
6771                  if True: 
6772                      # Minimise 
6773                      RDR.opt_max_iterations = int(1e2) 
6774                      RDR.minimise_execute(methods=methods, model=MODEL_CR72, analysis='min_ind', analysis_from='grid_setup_ind', list_glob_ini=list_glob_ini, force=True) 
6775   
6776                  #print asd 
6777   
6778          # Plot statistics. 
6779          # Try plot some minimisation correlations. 
6780          if True: 
6781              selections = [None, ':2,3'] 
6782              for selection in selections: 
6783                  # Collect param values. 
6784                  analysis = 'min_ind' 
6785                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6786                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6787   
6788                  fig1 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6789                  fig2 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6790                  corr_data = [fig1, fig2] 
6791   
6792                  write_stats = True 
6793                  RDR.plot_min_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6794   
6795                  # Open stat file. 
6796                  if write_stats: 
6797                      for i, corr_data_i in enumerate(corr_data): 
6798                          data, methods, glob_inis = corr_data[i] 
6799                          data_x, data_y = data 
6800                          method_x, method_y = methods 
6801                          glob_ini_x, glob_ini_y = glob_inis 
6802   
6803                          file_name_ini = '%s_%s_%s_%s_%s' % (analysis, method_x, glob_ini_x, method_y, glob_ini_y) 
6804   
6805                          if selection == None: 
6806                              file_name = file_name_ini + '_all.txt' 
6807                          else: 
6808                              file_name = file_name_ini + '_sel.txt' 
6809                          path = RDR.results_dir 
6810                          data = extract_data(file=file_name, dir=path) 
6811   
6812                          # Loop over the lines. 
6813                          for i, data_i in enumerate(data): 
6814                              print(i, data_i) 
6815   
6816          # Try plot some minimisation statistics. 
6817          if True: 
6818              # Collect param values. 
6819              #selections = [None, ':2,3'] 
6820              selections = [None, ':2,3'] 
6821              for selection in selections: 
6822                  analysis = 'min_ind' 
6823                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6824                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6825   
6826                  # Get param stats. 
6827                  min_stat_dic = RDR.get_min_stat_dic(list_r2eff_dics=[min_ft_sel, min_mdd_sel], list_glob_ini=[128, 126]) 
6828   
6829                  ## Plot R2eff stats 
6830                  write_stats = True 
6831                  RDR.plot_min_stat(min_stat_dic=min_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6832   
6833                  # Open stat file. 
6834                  if write_stats: 
6835                      if selection == None: 
6836                          file_name = '%s_stat_all.txt' % (analysis) 
6837                      else: 
6838                          file_name = '%s_stat_sel.txt' % (analysis) 
6839                      path = RDR.results_dir 
6840                      data = extract_data(file=file_name, dir=path) 
6841   
6842                      # Loop over the lines. 
6843                      for i, data_i in enumerate(data): 
6844                          print(i, data_i) 
6845   
6846   
6847          # Do minimisation clustered. 
6848          if True: 
6849              methods = ['FT', 'MDD'] 
6850              # Now calculate R2eff. 
6851              RDR.calc_r2eff(methods=methods, list_glob_ini=[128, 126]) 
6852   
6853              min_methods = [['FT'], ['MDD']] 
6854              min_list_glob_ini = [[128], list(range(126, 130, 2))[::-1]] 
6855   
6856              #min_methods = [['FT']] 
6857              #min_list_glob_ini = [[128]] 
6858              selection = ':2,3' 
6859   
6860              for i, methods in enumerate(min_methods): 
6861                  list_glob_ini = min_list_glob_ini[i] 
6862   
6863                  if True: 
6864                      # First get data. 
6865                      if True: 
6866                          # First load all data. 
6867                          RDR.calc_r2eff(methods=methods, list_glob_ini=list_glob_ini) 
6868   
6869                      # Then select spins. 
6870                      if True: 
6871                          # Deselect all spins. 
6872                          RDR.deselect_all(methods=methods, model='setup', model_from=MODEL_R2EFF, analysis='grid_setup', analysis_from='int', list_glob_ini=list_glob_ini, force=True) 
6873   
6874                          RDR.select_spin(spin_id=selection, methods=methods, model='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6875   
6876                      # Then preset values. 
6877                      if True: 
6878                          # Set k_AB for Grid search. 
6879                          RDR.value_set(methods=methods, val=1000., param='kex', model=MODEL_CR72, model_from='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6880                          RDR.value_set(methods=methods, val=0.95, param='pA', model=MODEL_CR72, model_from='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6881   
6882                      # Then set R20 
6883                      if True: 
6884                          # Set R20 from min R2eff in preparation for Grid search. 
6885                          RDR.r20_from_min_r2eff(methods=methods, model=MODEL_CR72, analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6886   
6887                      # Check and print parameters. 
6888                      if True: 
6889                          # Print for pipe name 
6890                          method = methods[0] 
6891                          glob_ini = list_glob_ini[0] 
6892   
6893                          test_pipe_name = RDR.name_pipe(method=method, model=MODEL_CR72, analysis='grid_setup', glob_ini=glob_ini) 
6894                          RDR.spin_display_params(pipe_name=test_pipe_name) 
6895   
6896                      # Then Grid search. 
6897                      if True: 
6898                          # Do Grid search. 
6899                          RDR.minimise_grid_search(inc=200, verbosity=1, methods=methods, model=MODEL_CR72, analysis='grid', analysis_from='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6900   
6901                      # Then cluster spins. 
6902                      if True: 
6903                          RDR.cluster_spins(spin_id=selection, methods=methods, model=MODEL_CR72, analysis='grid', list_glob_ini=list_glob_ini, force=True) 
6904   
6905                  # Then Minimise. 
6906                  if True: 
6907                      # Minimise 
6908                      RDR.opt_max_iterations = int(1e2) 
6909                      RDR.minimise_execute(methods=methods, model=MODEL_CR72, analysis='min', analysis_from='grid', list_glob_ini=list_glob_ini, force=False) 
6910   
6911          # Plot statistics. 
6912          # Try plot some minimisation correlations. 
6913          if True: 
6914              selection = ':2,3' 
6915              # Collect param values. 
6916              analysis = 'min' 
6917              min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6918              min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6919   
6920              fig1 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6921              fig2 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6922              corr_data = [fig1, fig2] 
6923   
6924              write_stats = True 
6925              RDR.plot_min_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6926   
6927              # Open stat file. 
6928              if write_stats: 
6929                  for i, corr_data_i in enumerate(corr_data): 
6930                      data, methods, glob_inis = corr_data[i] 
6931                      data_x, data_y = data 
6932                      method_x, method_y = methods 
6933                      glob_ini_x, glob_ini_y = glob_inis 
6934   
6935                      file_name_ini = '%s_%s_%s_%s_%s' % (analysis, method_x, glob_ini_x, method_y, glob_ini_y) 
6936   
6937                      if selection == None: 
6938                          file_name = file_name_ini + '_all.txt' 
6939                      else: 
6940                          file_name = file_name_ini + '_sel.txt' 
6941                      path = RDR.results_dir 
6942                      data = extract_data(file=file_name, dir=path) 
6943   
6944                      # Loop over the lines. 
6945                      for i, data_i in enumerate(data): 
6946                          print(i, data_i) 
6947   
6948          # Try plot some minimisation statistics. 
6949          if True: 
6950              # Collect param values. 
6951              selections = [':2,3'] 
6952              for selection in selections: 
6953                  analysis = 'min' 
6954                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6955                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6956   
6957                  # Get param stats. 
6958                  min_stat_dic = RDR.get_min_stat_dic(list_r2eff_dics=[min_ft_sel, min_mdd_sel], list_glob_ini=[128, 126]) 
6959   
6960                  ## Plot R2eff stats 
6961                  write_stats = True 
6962                  RDR.plot_min_stat(min_stat_dic=min_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6963   
6964                  # Open stat file. 
6965                  if write_stats: 
6966                      if selection == None: 
6967                          file_name = '%s_stat_all.txt' % (analysis) 
6968                      else: 
6969                          file_name = '%s_stat_sel.txt' % (analysis) 
6970                      path = RDR.results_dir 
6971                      data = extract_data(file=file_name, dir=path) 
6972   
6973                      # Loop over the lines. 
6974                      for i, data_i in enumerate(data): 
6975                          print(i, data_i) 
6976   
6977   
6978 -    def test_r1rho_kjaergaard_auto(self): 
6979          """Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
6980   
6981          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
6982   
6983          This uses the automatic analysis. 
6984   
6985          """ 
6986   
6987          # Cluster residues 
6988          cluster_ids = [ 
6989          ":13@N", 
6990          ":15@N", 
6991          ":16@N", 
6992          ":25@N", 
6993          ":26@N", 
6994          ":28@N", 
6995          ":39@N", 
6996          ":40@N", 
6997          ":41@N", 
6998          ":43@N", 
6999          ":44@N", 
7000          ":45@N", 
7001          ":49@N", 
7002          ":52@N", 
7003          ":53@N"] 
7004   
7005          # Load the data. 
7006          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids) 
7007   
7008          # Test some of the sequence. 
7009          self.assertEqual(len(cdp.mol), 1) 
7010          self.assertEqual(cdp.mol[0].name, None) 
7011          self.assertEqual(len(cdp.mol[0].res), 48) 
7012   
7013          # Test the chemical shift data. 
7014          cs = [122.223, 122.162, 114.250, 125.852, 118.626, 117.449, 119.999, 122.610, 118.602, 118.291, 115.393, 
7015          121.288, 117.448, 116.378, 116.316, 117.263, 122.211, 118.748, 118.103, 119.421, 119.317, 119.386, 117.279, 
7016          122.103, 120.038, 116.698, 111.811, 118.639, 118.285, 121.318, 117.770, 119.948, 119.759, 118.314, 118.160, 
7017          121.442, 118.714, 113.080, 125.706, 119.183, 120.966, 122.361, 126.675, 117.069, 120.875, 109.372, 119.811, 126.048] 
7018   
7019          i = 0 
7020          for spin, spin_id in spin_loop(return_id=True): 
7021              # Check the chemical shift. 
7022              self.assertEqual(spin.chemical_shift, cs[i]) 
7023   
7024              # Increment the index. 
7025              i += 1 
7026   
7027          # Initialize counter 
7028          i = 0 
7029          j = 0 
7030          # Count instances of select/deselect 
7031          for curspin, mol_name, res_num, res_name, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
7032              if curspin.select == True: 
7033                  i += 1 
7034              if curspin.select == False: 
7035                  j += 1 
7036   
7037          # Test number of selected/deselected spins. 
7038          self.assertEqual(i, len(cluster_ids)) 
7039          self.assertEqual(j, 48-len(cluster_ids)) 
7040   
7041          # Check the initial setup. 
7042          self.assertEqual(cdp.mol[0].res[7].num, 13) 
7043          self.assertEqual(cdp.mol[0].res[7].spin[0].kex, ds.guess[':13@N'][6]) 
7044          self.assertEqual(cdp.mol[0].res[7].spin[0].ri_data['R1'], ds.ref[':13@N'][2]) 
7045   
7046          self.assertEqual(cdp.mol[0].res[9].num, 15) 
7047          self.assertEqual(cdp.mol[0].res[9].spin[0].kex, ds.guess[':15@N'][6]) 
7048          self.assertEqual(cdp.mol[0].res[9].spin[0].ri_data['R1'], ds.ref[':15@N'][2]) 
7049   
7050          self.assertEqual(cdp.mol[0].res[10].num, 16) 
7051          self.assertEqual(cdp.mol[0].res[10].spin[0].kex, ds.guess[':16@N'][6]) 
7052          self.assert_(hasattr(cdp.mol[0].res[10].spin[0], 'ri_data')) 
7053   
7054          self.assertEqual(cdp.mol[0].res[16].num, 25) 
7055          self.assertEqual(cdp.mol[0].res[16].spin[0].kex, ds.guess[':25@N'][6]) 
7056          self.assert_(hasattr(cdp.mol[0].res[16].spin[0], 'ri_data')) 
7057   
7058          self.assertEqual(cdp.mol[0].res[17].num, 26) 
7059          self.assertEqual(cdp.mol[0].res[17].spin[0].kex, ds.guess[':26@N'][6]) 
7060          self.assert_(hasattr(cdp.mol[0].res[17].spin[0], 'ri_data')) 
7061   
7062          self.assertEqual(cdp.mol[0].res[19].num, 28) 
7063          self.assertEqual(cdp.mol[0].res[19].spin[0].kex, ds.guess[':28@N'][6]) 
7064          self.assert_(hasattr(cdp.mol[0].res[19].spin[0], 'ri_data')) 
7065   
7066          self.assertEqual(cdp.mol[0].res[29].num, 39) 
7067          self.assertEqual(cdp.mol[0].res[29].spin[0].kex, ds.guess[':39@N'][6]) 
7068          self.assert_(hasattr(cdp.mol[0].res[29].spin[0], 'ri_data')) 
7069   
7070          self.assertEqual(cdp.mol[0].res[30].num, 40) 
7071          self.assertEqual(cdp.mol[0].res[30].spin[0].kex, ds.guess[':40@N'][6]) 
7072          self.assert_(hasattr(cdp.mol[0].res[30].spin[0], 'ri_data')) 
7073   
7074          self.assertEqual(cdp.mol[0].res[31].num, 41) 
7075          self.assertEqual(cdp.mol[0].res[31].spin[0].kex, ds.guess[':41@N'][6]) 
7076          self.assert_(hasattr(cdp.mol[0].res[31].spin[0], 'ri_data')) 
7077   
7078          self.assertEqual(cdp.mol[0].res[33].num, 43) 
7079          self.assertEqual(cdp.mol[0].res[33].spin[0].kex, ds.guess[':43@N'][6]) 
7080          self.assert_(hasattr(cdp.mol[0].res[33].spin[0], 'ri_data')) 
7081   
7082          self.assertEqual(cdp.mol[0].res[34].num, 44) 
7083          self.assertEqual(cdp.mol[0].res[34].spin[0].kex, ds.guess[':44@N'][6]) 
7084          self.assert_(hasattr(cdp.mol[0].res[34].spin[0], 'ri_data')) 
7085   
7086          self.assertEqual(cdp.mol[0].res[35].num, 45) 
7087          self.assertEqual(cdp.mol[0].res[35].spin[0].kex, ds.guess[':45@N'][6]) 
7088          self.assert_(hasattr(cdp.mol[0].res[35].spin[0], 'ri_data')) 
7089   
7090          self.assertEqual(cdp.mol[0].res[38].num, 49) 
7091          self.assertEqual(cdp.mol[0].res[38].spin[0].kex, ds.guess[':49@N'][6]) 
7092          self.assert_(hasattr(cdp.mol[0].res[38].spin[0], 'ri_data')) 
7093   
7094          self.assertEqual(cdp.mol[0].res[41].num, 52) 
7095          self.assertEqual(cdp.mol[0].res[41].spin[0].kex, ds.guess[':52@N'][6]) 
7096          self.assert_(hasattr(cdp.mol[0].res[41].spin[0], 'ri_data')) 
7097   
7098          self.assertEqual(cdp.mol[0].res[42].num, 53) 
7099          self.assertEqual(cdp.mol[0].res[42].spin[0].kex, ds.guess[':53@N'][6]) 
7100          self.assert_(hasattr(cdp.mol[0].res[42].spin[0], 'ri_data')) 
7101   
7102          # The dispersion models. 
7103          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
7104   
7105          # The grid search size (the number of increments per dimension). 
7106          GRID_INC = 4 
7107   
7108          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7109          MC_NUM = 3 
7110   
7111          # Model selection technique. 
7112          MODSEL = 'AIC' 
7113   
7114          # Execute the auto-analysis (fast). 
7115          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7116          OPT_FUNC_TOL = 1e-1 
7117          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7118          OPT_MAX_ITERATIONS = 1000 
7119          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7120   
7121          result_dir_name = ds.tmpdir 
7122   
7123          # Make all spins free 
7124          for curspin in cluster_ids: 
7125              self.interpreter.relax_disp.cluster('free spins', curspin) 
7126              # Shut them down 
7127              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
7128   
7129          # Select only a subset of spins for global fitting 
7130          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
7131          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
7132   
7133          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
7134          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
7135   
7136          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
7137          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
7138   
7139          # Run the analysis. 
7140          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
7141   
7142          # Check the kex value of residue 52 
7143          #self.assertAlmostEqual(cdp.mol[0].res[41].spin[0].kex, ds.ref[':52@N'][6]) 
7144   
7145          # Print results for each model. 
7146          print("\n\n################") 
7147          print("Printing results") 
7148          print("################\n") 
7149          for model in MODELS: 
7150              # Skip R2eff model. 
7151              if model == MODEL_R2EFF: 
7152                  continue 
7153   
7154              # Switch to pipe. 
7155              self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
7156              print("\nModel: %s" % (model)) 
7157   
7158              # Loop over the spins. 
7159              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7160                  # Generate spin string. 
7161                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
7162   
7163                  # Loop over the parameters. 
7164                  print("Optimised parameters for spin: %s" % (spin_string)) 
7165                  for param in cur_spin.params + ['chi2']: 
7166                      # Get the value. 
7167                      if param in ['r1', 'r2']: 
7168                          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
7169                              # Generate the R20 key. 
7170                              r20_key = generate_r20_key(exp_type=exp_type, frq=frq) 
7171   
7172                              # Get the value. 
7173                              value = getattr(cur_spin, param)[r20_key] 
7174   
7175                              # Print value. 
7176                              print("%-10s %-6s %-6s %3.3f" % ("Parameter:", param, "Value:", value)) 
7177   
7178                      # For all other parameters. 
7179                      else: 
7180                          # Get the value. 
7181                          value = getattr(cur_spin, param) 
7182   
7183                          # Print value. 
7184                          print("%-10s %-6s %-6s %3.3f" % ("Parameter:", param, "Value:", value)) 
7185   
7186          # Print the final pipe. 
7187          self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % ('final')) 
7188          print("\nFinal pipe") 
7189   
7190   
7191 -    def test_r1rho_kjaergaard_auto_check_graphs(self): 
7192          """Check of plot_disp_curves() function, after optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'R2eff' model. 
7193   
7194          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
7195   
7196          This uses the automatic analysis. 
7197   
7198          """ 
7199   
7200          # Cluster residues 
7201          cluster_ids = [ 
7202          ":52@N"] 
7203   
7204          # Load the data. 
7205          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids) 
7206   
7207          # The dispersion models. 
7208          MODELS = [MODEL_R2EFF] 
7209   
7210          # The grid search size (the number of increments per dimension). 
7211          GRID_INC = 4 
7212   
7213          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7214          MC_NUM = 3 
7215   
7216          # Model selection technique. 
7217          MODSEL = 'AIC' 
7218   
7219          # Execute the auto-analysis (fast). 
7220          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7221          OPT_FUNC_TOL = 1e-1 
7222          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7223          OPT_MAX_ITERATIONS = 1000 
7224          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7225   
7226          result_dir_name = ds.tmpdir 
7227   
7228          # Make all spins free 
7229          for curspin in cluster_ids: 
7230              self.interpreter.relax_disp.cluster('free spins', curspin) 
7231              # Shut them down 
7232              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
7233   
7234          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
7235   
7236          # Run the analysis. 
7237          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
7238   
7239          # Check the graphs produced. 
7240          graph_comb = [ 
7241          [Y_AXIS_R2_EFF, X_AXIS_DISP, INTERPOLATE_DISP], 
7242          [Y_AXIS_R2_EFF, X_AXIS_THETA, INTERPOLATE_DISP], 
7243          [Y_AXIS_R2_R1RHO, X_AXIS_W_EFF, INTERPOLATE_DISP], 
7244          [Y_AXIS_R2_EFF, X_AXIS_THETA, INTERPOLATE_OFFSET] 
7245          ] 
7246   
7247          # Define expected folder names. 
7248          result_folders = MODELS 
7249   
7250          # Assign spin_id. 
7251          spin_id = ':52@N' 
7252   
7253          # Loop over result folders. 
7254          for result_folder in result_folders: 
7255              # Skip the model R2eff, which does not produce graphs. 
7256              if result_folder == MODEL_R2EFF: 
7257                  continue 
7258   
7259              # Loop over graphs. 
7260              for y_axis, x_axis, interpolate in graph_comb: 
7261                  # Determine file name: 
7262                  file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
7263   
7264                  # Make the file name. 
7265                  file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
7266   
7267                  # Get the file path. 
7268                  file_path = get_file_path(file_name, result_dir_name+sep+result_folder) 
7269   
7270                  print("Testing file access to graph: %s"%file_path) 
7271                  self.assert_(access(file_path, F_OK)) 
7272   
7273          # Start testing all possible combinations of graphs. 
7274          y_axis_types = [Y_AXIS_R2_EFF, Y_AXIS_R2_R1RHO] 
7275          x_axis_types = [X_AXIS_DISP, X_AXIS_THETA, X_AXIS_W_EFF] 
7276          interpolate_types = [INTERPOLATE_DISP, INTERPOLATE_OFFSET] 
7277   
7278          result_dir_name = ds.tmpdir 
7279   
7280          # Loop through all possible combinations of y_axis, x_axis and interpolation. 
7281          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep+'check_graphs' 
7282   
7283          for result_folder in result_folders: 
7284              # Skip the model R2eff, which does not produce graphs. 
7285              if result_folder == MODEL_R2EFF: 
7286                  continue 
7287   
7288              for y_axis in y_axis_types: 
7289                  for x_axis in x_axis_types: 
7290                      for interpolate in interpolate_types: 
7291                          # Determine file name: 
7292                          file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
7293   
7294                          # Make the file name. 
7295                          file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
7296   
7297                          # Write the curves. 
7298                          dir = result_dir_name+sep+result_folder 
7299                          print("Plotting combination of %s, %s, %s"%(y_axis, x_axis, interpolate)) 
7300                          self.interpreter.relax_disp.plot_disp_curves(dir=dir, y_axis=y_axis, x_axis=x_axis, interpolate=interpolate, force=True) 
7301   
7302                          # Get the file path. 
7303                          file_path = get_file_path(file_name, dir) 
7304   
7305                          # Test the plot file exists. 
7306                          print("Testing file access to graph: %s"%file_path) 
7307                          self.assert_(access(file_path, F_OK)) 
7308   
7309                          # Now open, and compare content, line by line. 
7310                          file_prod = open(file_path) 
7311                          lines_prod = file_prod.readlines() 
7312                          file_prod.close() 
7313   
7314                          # Define file to compare against. 
7315                          dir_comp = data_path+sep+result_folder 
7316                          file_path_comp = get_file_path(file_name, dir_comp) 
7317                          file_comp = open(file_path_comp) 
7318                          lines_comp = file_comp.readlines() 
7319                          file_comp.close() 
7320   
7321                          # Assert number of lines is equal. 
7322                          self.assertEqual(len(lines_prod), len(lines_comp)) 
7323                          for j in range(len(lines_prod)): 
7324                              # Make the string test 
7325                              first_char = lines_prod[j][0] 
7326                              if first_char in ["@", "&"]: 
7327                                  self.assertEqual(lines_prod[j], lines_comp[j]) 
7328                              else: 
7329                                  # Split string in x, y, error. 
7330                                  # The error would change per run. 
7331                                  x_prod, y_prod, y_prod_err = lines_prod[j].split() 
7332                                  x_comp, y_comp, y_comp_err = lines_comp[j].split() 
7333                                  self.assertAlmostEqual(float(x_prod), float(x_comp)) 
7334                                  self.assertAlmostEqual(float(y_prod), float(y_comp)) 
7335   
7336   
7337 -    def test_r1rho_kjaergaard_missing_r1(self): 
7338          """Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
7339   
7340          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
7341   
7342          This uses the automatic analysis, with missing loading R1. 
7343   
7344          """ 
7345   
7346          # Cluster residues 
7347          cluster_ids = [ 
7348          ":13@N", 
7349          ":15@N", 
7350          ":16@N", 
7351          ":25@N", 
7352          ":26@N", 
7353          ":28@N", 
7354          ":39@N", 
7355          ":40@N", 
7356          ":41@N", 
7357          ":43@N", 
7358          ":44@N", 
7359          ":45@N", 
7360          ":49@N", 
7361          ":52@N", 
7362          ":53@N"] 
7363   
7364          # Load the data. 
7365          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
7366   
7367          # The dispersion models. 
7368          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
7369   
7370          # The grid search size (the number of increments per dimension). 
7371          GRID_INC = None 
7372   
7373          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7374          MC_NUM = 3 
7375   
7376          # Model selection technique. 
7377          MODSEL = 'AIC' 
7378   
7379          # Execute the auto-analysis (fast). 
7380          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7381          OPT_FUNC_TOL = 1e-25 
7382          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7383          OPT_MAX_ITERATIONS = 10000000 
7384          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7385   
7386          result_dir_name = ds.tmpdir 
7387   
7388          # Make all spins free 
7389          for curspin in cluster_ids: 
7390              self.interpreter.relax_disp.cluster('free spins', curspin) 
7391              # Shut them down 
7392              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
7393   
7394          # Select only a subset of spins for global fitting 
7395          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
7396          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
7397   
7398          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
7399          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
7400   
7401          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
7402          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
7403   
7404          # Point to directory with R2eff values, with 2000 MC simulations. 
7405          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000" 
7406   
7407          r1_fit = True 
7408   
7409          # Run the analysis. 
7410          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, pre_run_dir=prev_data_path, r1_fit=r1_fit) 
7411   
7412          # Verify the data. 
7413          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='MC2000') 
7414   
7415   
7416 -    def test_r2eff_read(self): 
7417          """Test the operation of the relax_disp.r2eff_read user function.""" 
7418   
7419          # The path to the data files. 
7420          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'800_MHz' 
7421   
7422          # Read the sequence data. 
7423          self.interpreter.sequence.read(file='66.667.in', dir=data_path, res_num_col=1) 
7424   
7425          # The ID. 
7426          id = 'test' 
7427   
7428          # Set up the metadata. 
7429          self.interpreter.spectrometer.frequency(id=id, frq=800e6) 
7430          self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
7431   
7432          # Try reading the file. 
7433          self.interpreter.relax_disp.r2eff_read(id=id, file='66.667.in', dir=data_path, disp_frq=66.667, res_num_col=1, data_col=2, error_col=3) 
7434   
7435          # Check the global data. 
7436          data = [ 
7437              ['cpmg_frqs', {'test': 66.667}], 
7438              ['cpmg_frqs_list', [66.667]], 
7439              ['dispersion_points', 1], 
7440              ['exp_type', {'test': 'SQ CPMG'}], 
7441              ['exp_type_list', ['SQ CPMG']], 
7442              ['spectrometer_frq', {'test': 800000000.0}], 
7443              ['spectrometer_frq_count', 1], 
7444              ['spectrometer_frq_list', [800000000.0]], 
7445              ['spectrum_ids', ['test']] 
7446          ] 
7447          for name, value in data: 
7448              # Does it exist? 
7449              self.assert_(hasattr(cdp, name)) 
7450   
7451              # Check the object. 
7452              obj = getattr(cdp, name) 
7453              self.assertEqual(obj, value) 
7454   
7455          # Check the spin data. 
7456          data = [ 
7457              [1,       2.3035747e+04, 8.5467725e+01], 
7458              [2,       9.9629762e+04, 2.8322033e+02], 
7459              [3,       9.5663137e+04, 2.8632929e+02], 
7460              [4,       1.7089893e+05, 3.1089428e+02], 
7461              [5,       4.7323876e+04, 1.0084269e+02], 
7462              [6,       2.0199122e+04, 1.0135220e+02], 
7463              [7,       1.6655488e+05, 3.1609061e+02], 
7464              [8,       9.0061074e+04, 1.9176585e+02], 
7465              [10,      8.4726204e+04, 2.8898155e+02], 
7466              [11,      1.5050233e+05, 4.3138029e+02], 
7467              [12,      9.2998531e+04, 3.0440191e+02], 
7468              [13,      1.6343507e+05, 3.3144097e+02], 
7469              [14,      1.0137301e+05, 3.7314642e+02], 
7470              [15,      8.3407837e+04, 1.6546473e+02], 
7471              [16,      1.3819126e+05, 3.3388517e+02], 
7472              [17,      1.1010490e+05, 3.5639222e+02], 
7473              [18,      9.4324035e+04, 3.2343585e+02], 
7474              [19,      1.1135179e+05, 3.0706671e+02], 
7475              [20,      7.6339410e+04, 1.7377460e+02], 
7476              [21,      6.2008453e+04, 1.7327150e+02], 
7477              [22,      1.0590404e+05, 2.4814635e+02], 
7478              [23,      1.0630198e+05, 2.3601100e+02], 
7479              [24,      7.2996320e+04, 1.4952465e+02], 
7480              [25,      9.5486742e+04, 2.7080766e+02], 
7481              [26,      5.8067989e+04, 1.6820462e+02], 
7482              [27,     -1.7168510e+04, 2.2519560e+02], 
7483              [28,      1.6891473e+05, 2.3497525e+02], 
7484              [29,      9.4038555e+04, 2.0357593e+02], 
7485              [30,      2.1386951e+04, 2.2153532e+02], 
7486              [31,      9.3982899e+04, 2.0937056e+02], 
7487              [32,      8.6097484e+04, 2.3868467e+02], 
7488              [33,      1.0194337e+05, 2.7370704e+02], 
7489              [34,      8.5683111e+04, 2.0838076e+02], 
7490              [35,      8.6985768e+04, 2.0889310e+02], 
7491              [36,      8.6011237e+04, 1.7498390e+02], 
7492              [37,      1.0984097e+05, 2.7622998e+02], 
7493              [38,      8.7017879e+04, 2.6547994e+02], 
7494              [39,      9.1682649e+04, 5.2777676e+02], 
7495              [40,      7.6370440e+04, 1.9873214e+02], 
7496              [41,      9.1393531e+04, 2.4483824e+02], 
7497              [42,      1.1017111e+05, 2.8020699e+02], 
7498              [43,      9.4552366e+04, 3.4394150e+02], 
7499              [44,      1.2858281e+05, 6.8449252e+02], 
7500              [45,      7.4583525e+04, 1.9544210e+02], 
7501              [46,      9.2087490e+04, 2.0491066e+02], 
7502              [47,      9.7507255e+04, 2.5162839e+02], 
7503              [48,      1.0033842e+05, 2.7566430e+02], 
7504              [49,      1.3048305e+05, 2.6797466e+02], 
7505              [50,      1.0546796e+05, 1.9304384e+02], 
7506              [51,      9.3099697e+04, 2.0773311e+02], 
7507              [52,      4.6863758e+04, 1.3169068e+02], 
7508              [53,      6.1055806e+04, 1.5448477e+02], 
7509              [55,      6.8629994e+04, 1.6868673e+02], 
7510              [56,      1.1005552e+05, 2.1940465e+02], 
7511              [57,      1.0572760e+05, 1.9768486e+02], 
7512              [58,      1.1176950e+05, 3.0009610e+02], 
7513              [59,      9.8758603e+04, 3.3803895e+02], 
7514              [60,      9.9517201e+04, 3.5137994e+02], 
7515              [61,      5.4357946e+04, 2.5896579e+02], 
7516              [62,      1.0899978e+05, 2.8720371e+02], 
7517              [63,      8.4549759e+04, 4.1401837e+02], 
7518              [64,      5.5014550e+04, 2.1135781e+02], 
7519              [65,      8.0569666e+04, 2.3249709e+02], 
7520              [66,      1.2936610e+05, 3.5218725e+02], 
7521              [67,      3.6438010e+04, 8.7924003e+01], 
7522              [70,      3.8763157e+04, 1.3325040e+02], 
7523              [71,      8.5711411e+04, 2.9316183e+02], 
7524              [72,      3.3211541e+04, 1.2182123e+02], 
7525              [73,      3.2070576e+04, 1.2305430e+02] 
7526          ] 
7527          for res_num, value, error in data: 
7528              # Get the spin. 
7529              spin = return_spin(spin_id=":%s"%res_num) 
7530   
7531              # Check the values. 
7532              self.assertEqual(spin.r2eff['sq_cpmg_800.00000000_0.000_66.667'], value) 
7533              self.assertEqual(spin.r2eff_err['sq_cpmg_800.00000000_0.000_66.667'], error) 
7534   
7535   
7536 -    def test_r2eff_read_spin(self): 
7537          """Test the operation of the relax_disp.r2eff_read_spin user function.""" 
7538   
7539          # The path to the data files. 
7540          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Korzhnev_et_al_2005' 
7541   
7542          # Generate the sequence. 
7543          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='H') 
7544          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='N') 
7545          self.interpreter.spin.isotope('1H', spin_id='@H') 
7546          self.interpreter.spin.isotope('15N', spin_id='@N') 
7547   
7548          # Build the experiment IDs. 
7549          H_disp_points = [67.0, 133.0, 267.0, 400.0, 533.0, 667.0, 800.0, 933.0, 1067.0, 1600.0, 2133.0, 2667.0] 
7550          N_disp_points = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
7551          ids = [] 
7552          for value in H_disp_points: 
7553              ids.append('1H_CPMG_%s' % value) 
7554          for value in N_disp_points: 
7555              ids.append('15N_CPMG_%s' % value) 
7556          print("\n\nThe experiment IDs are %s." % ids) 
7557   
7558          # Set up the metadata for the experiments. 
7559          for id in ids: 
7560              self.interpreter.spectrometer.frequency(id=id, frq=500e6) 
7561              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
7562          for value in H_disp_points: 
7563              self.interpreter.relax_disp.cpmg_setup(spectrum_id='1H_CPMG_%s' % value, cpmg_frq=value) 
7564          for value in N_disp_points: 
7565              self.interpreter.relax_disp.cpmg_setup(spectrum_id='15N_CPMG_%s' % value, cpmg_frq=value) 
7566   
7567          # Loop over the experiments. 
7568          for id, file, spin_id in [['1H_CPMG', 'hs_500.res', ':9@H'], ['15N_CPMG', 'ns_500.res', ':9@N']]: 
7569              # Try reading the file. 
7570              self.interpreter.relax_disp.r2eff_read_spin(id=id, file=file, dir=data_path, spin_id=spin_id, disp_point_col=1, data_col=2, error_col=3) 
7571   
7572          # Check the global data. 
7573          data = [ 
7574              ['cpmg_frqs', {'1H_CPMG_667.0': 667.0, '1H_CPMG_1067.0': 1067.0, '15N_CPMG_350.0': 350.0, '1H_CPMG_933.0': 933.0, '15N_CPMG_50.0': 50.0, '15N_CPMG_100.0': 100.0, '1H_CPMG_400.0': 400.0, '1H_CPMG_533.0': 533.0, '1H_CPMG_800.0': 800.0, '15N_CPMG_900.0': 900.0, '15N_CPMG_150.0': 150.0, '15N_CPMG_800.0': 800.0, '1H_CPMG_267.0': 267.0, '1H_CPMG_2667.0': 2667.0, '15N_CPMG_300.0': 300.0, '1H_CPMG_133.0': 133.0, '15N_CPMG_700.0': 700.0, '1H_CPMG_67.0': 67.0, '15N_CPMG_400.0': 400.0, '15N_CPMG_250.0': 250.0, '1H_CPMG_2133.0': 2133.0, '1H_CPMG_1600.0': 1600.0, '15N_CPMG_200.0': 200.0, '15N_CPMG_1000.0': 1000.0, '15N_CPMG_500.0': 500.0, '15N_CPMG_600.0': 600.0}], 
7575              ['cpmg_frqs_list', [50.0, 67.0, 100.0, 133.0, 150.0, 200.0, 250.0, 267.0, 300.0, 350.0, 400.0, 500.0, 533.0, 600.0, 667.0, 700.0, 800.0, 900.0, 933.0, 1000.0, 1067.0, 1600.0, 2133.0, 2667.0]], 
7576              ['dispersion_points', 24], 
7577              ['exp_type', {'1H_CPMG_667.0': 'SQ CPMG', '1H_CPMG_1067.0': 'SQ CPMG', '15N_CPMG_350.0': 'SQ CPMG', '1H_CPMG_933.0': 'SQ CPMG', '15N_CPMG_50.0': 'SQ CPMG', '15N_CPMG_100.0': 'SQ CPMG', '1H_CPMG_400.0': 'SQ CPMG', '1H_CPMG_533.0': 'SQ CPMG', '1H_CPMG_800.0': 'SQ CPMG', '15N_CPMG_900.0': 'SQ CPMG', '15N_CPMG_150.0': 'SQ CPMG', '15N_CPMG_800.0': 'SQ CPMG', '1H_CPMG_267.0': 'SQ CPMG', '1H_CPMG_2667.0': 'SQ CPMG', '15N_CPMG_300.0': 'SQ CPMG', '1H_CPMG_133.0': 'SQ CPMG', '15N_CPMG_700.0': 'SQ CPMG', '1H_CPMG_67.0': 'SQ CPMG', '15N_CPMG_400.0': 'SQ CPMG', '15N_CPMG_250.0': 'SQ CPMG', '1H_CPMG_2133.0': 'SQ CPMG', '1H_CPMG_1600.0': 'SQ CPMG', '15N_CPMG_200.0': 'SQ CPMG', '15N_CPMG_1000.0': 'SQ CPMG', '15N_CPMG_500.0': 'SQ CPMG', '15N_CPMG_600.0': 'SQ CPMG'}], 
7578              ['exp_type_list', ['SQ CPMG']], 
7579              ['spectrometer_frq', {'1H_CPMG_667.0': 500000000.0, '1H_CPMG_1067.0': 500000000.0, '15N_CPMG_350.0': 500000000.0, '1H_CPMG_933.0': 500000000.0, '15N_CPMG_50.0': 500000000.0, '15N_CPMG_100.0': 500000000.0, '1H_CPMG_400.0': 500000000.0, '1H_CPMG_533.0': 500000000.0, '1H_CPMG_800.0': 500000000.0, '15N_CPMG_900.0': 500000000.0, '15N_CPMG_150.0': 500000000.0, '15N_CPMG_800.0': 500000000.0, '1H_CPMG_267.0': 500000000.0, '1H_CPMG_2667.0': 500000000.0, '15N_CPMG_300.0': 500000000.0, '1H_CPMG_133.0': 500000000.0, '15N_CPMG_700.0': 500000000.0, '1H_CPMG_67.0': 500000000.0, '15N_CPMG_400.0': 500000000.0, '15N_CPMG_250.0': 500000000.0, '1H_CPMG_2133.0': 500000000.0, '1H_CPMG_1600.0': 500000000.0, '15N_CPMG_200.0': 500000000.0, '15N_CPMG_1000.0': 500000000.0, '15N_CPMG_500.0': 500000000.0, '15N_CPMG_600.0': 500000000.0}], 
7580              ['spectrometer_frq_count', 1], 
7581              ['spectrometer_frq_list', [500000000.0]], 
7582              ['spectrum_ids', ['1H_CPMG_67.0', '1H_CPMG_133.0', '1H_CPMG_267.0', '1H_CPMG_400.0', '1H_CPMG_533.0', '1H_CPMG_667.0', '1H_CPMG_800.0', '1H_CPMG_933.0', '1H_CPMG_1067.0', '1H_CPMG_1600.0', '1H_CPMG_2133.0', '1H_CPMG_2667.0', '15N_CPMG_50.0', '15N_CPMG_100.0', '15N_CPMG_150.0', '15N_CPMG_200.0', '15N_CPMG_250.0', '15N_CPMG_300.0', '15N_CPMG_350.0', '15N_CPMG_400.0', '15N_CPMG_500.0', '15N_CPMG_600.0', '15N_CPMG_700.0', '15N_CPMG_800.0', '15N_CPMG_900.0', '15N_CPMG_1000.0']] 
7583          ] 
7584          for name, value in data: 
7585              # Does it exist? 
7586              self.assert_(hasattr(cdp, name)) 
7587   
7588              # Check the object. 
7589              obj = getattr(cdp, name) 
7590              if not isinstance(data, dict): 
7591                  self.assertEqual(obj, value) 
7592   
7593              # Check the global dictionary data. 
7594              else: 
7595                  for id in ids: 
7596                      self.assertEqual(obj[id], value[id]) 
7597   
7598          # Check the spin data. 
7599          h_data = [ 
7600              [  67.0,  21.47924,   0.42958], 
7601              [ 133.0,  16.73898,   0.33478], 
7602              [ 267.0,   9.97357,   0.19947], 
7603              [ 400.0,   8.23877,   0.24737], 
7604              [ 533.0,   7.59290,   0.24263], 
7605              [ 667.0,   7.45843,   0.24165], 
7606              [ 800.0,   7.11222,   0.23915], 
7607              [ 933.0,   7.40880,   0.24129], 
7608              [1067.0,   6.55191,   0.16629], 
7609              [1600.0,   6.72177,   0.23637], 
7610              [2133.0,   7.09629,   0.23904], 
7611              [2667.0,   7.14675,   0.23940] 
7612          ] 
7613          for disp_point, value, error in h_data: 
7614              id = 'sq_cpmg_500.00000000_0.000_%.3f' % disp_point 
7615              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
7616              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
7617          n_data = [ 
7618              [  50.0,  27.15767,   0.54315], 
7619              [ 100.0,  26.55781,   0.53116], 
7620              [ 150.0,  24.73462,   0.49469], 
7621              [ 200.0,  20.98617,   0.41972], 
7622              [ 250.0,  17.82442,   0.35649], 
7623              [ 300.0,  15.55352,   0.31107], 
7624              [ 350.0,  13.78958,   0.27579], 
7625              [ 400.0,  12.48334,   0.24967], 
7626              [ 500.0,  11.55724,   0.23114], 
7627              [ 600.0,  10.53874,   0.21077], 
7628              [ 700.0,  10.07395,   0.20148], 
7629              [ 800.0,   9.62952,   0.19259], 
7630              [ 900.0,   9.49994,   0.19000], 
7631              [1000.0,   8.71350,   0.17427] 
7632          ] 
7633          for disp_point, value, error in n_data: 
7634              id = 'sq_cpmg_500.00000000_0.000_%.3f' % disp_point 
7635              self.assertEqual(cdp.mol[0].res[0].spin[1].r2eff[id], value) 
7636              self.assertEqual(cdp.mol[0].res[0].spin[1].r2eff_err[id], error) 
7637   
7638   
7639 -    def test_r2eff_fit_fixed_time(self): 
7640          """Test the relaxation dispersion 'R2eff' model for fixed time data in the auto-analysis.""" 
7641   
7642          # Execute the script. 
7643          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r2eff_calc.py') 
7644   
7645   
7646 -    def test_read_r2eff(self): 
7647          """Test the reading of a file containing r2eff values.""" 
7648   
7649          # Create the sequence data, and name the spins. 
7650          self.interpreter.residue.create(1, 'Gly') 
7651          self.interpreter.residue.create(2, 'Gly') 
7652          self.interpreter.residue.create(3, 'Gly') 
7653   
7654          # Read the file. 
7655          self.interpreter.relax_data.read(ri_id='R2eff.600', ri_type='R2eff', frq=600*1e6, file='r2eff.out', dir=status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r2eff', res_num_col=1, res_name_col=2, data_col=3, error_col=4) 
7656   
7657          # Test the data. 
7658          self.assertEqual(cdp.mol[0].res[0].spin[0].ri_data['R2eff.600'], 15.000) 
7659          self.assertEqual(cdp.mol[0].res[1].spin[0].ri_data['R2eff.600'], 4.2003) 
7660          self.assertEqual(cdp.mol[0].res[2].spin[0].ri_data['R2eff.600'], 7.2385) 
7661   
7662   
7663 -    def test_r20_from_min_r2eff_cpmg(self): 
7664          """Test speeding up grid search. Support requst sr #3151 U{https://gna.org/support/index.php?3151}. 
7665   
7666          User function to set the R20 parameters in the default grid search using the minimum R2eff value. 
7667   
7668          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7669          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7670   
7671          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7672          Data is for experiment at 25 degree Celcius. 
7673          """ 
7674   
7675          # Base data setup. 
7676          pipe_name = 'base pipe' 
7677          pipe_type = 'relax_disp' 
7678          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7679          select_spin_index = list(range(0, 1)) 
7680          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7681   
7682          # Generate r20 key. 
7683          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
7684          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
7685   
7686          ## Now prepare for MODEL calculation. 
7687          MODEL = "CR72" 
7688   
7689          # Change pipe. 
7690          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
7691          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7692          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7693   
7694          # Then select model. 
7695          self.interpreter.relax_disp.select_model(model=MODEL) 
7696   
7697          # Set the R20 parameters in the default grid search using the minimum R2eff value. 
7698          self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
7699   
7700          # Test result, for normal run. 
7701          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7702              # Get the spin_params. 
7703              spin_params = spin.params 
7704   
7705              # Defined fixed values for testing. 
7706              if spin_id == ":10@N": 
7707                  self.assertEqual(spin.r2[r20_key_600], 20.282732526087106) 
7708                  self.assertEqual(spin.r2[r20_key_500], 18.475299724356649) 
7709   
7710              # Print out. 
7711              print("r2_600=%2.2f r2_500=%2.2f spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500], spin_id, resi, resn)) 
7712   
7713              # Testing the r2 values for the different fields are not the same. 
7714              self.assert_(spin.r2[r20_key_600] != spin.r2[r20_key_500]) 
7715   
7716              # Test values are larger than 0. 
7717              self.assert_(spin.r2[r20_key_600] > 0.0) 
7718              self.assert_(spin.r2[r20_key_500] > 0.0) 
7719   
7720              # Loop over the experiment settings. 
7721              r2eff_600 = [] 
7722              r2eff_500 = [] 
7723              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
7724                  # Create the data key. 
7725                  data_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
7726   
7727                  # Extract the r2 eff data. 
7728                  r2eff = spin.r2eff[data_key] 
7729                  if frq == 599.8908617*1E6: 
7730                      r2eff_600.append(r2eff) 
7731                  elif frq == 499.862139*1E6: 
7732                      r2eff_500.append(r2eff) 
7733   
7734              # Sort values. 
7735              r2eff_600.sort() 
7736              r2eff_500.sort() 
7737   
7738              # Test values again. 
7739              print("For r20 600MHz min r2eff=%3.3f."%(min(r2eff_600))) 
7740              print(r2eff_600) 
7741              self.assertEqual(spin.r2[r20_key_600], min(r2eff_600)) 
7742              print("") 
7743   
7744              print("For r20 500MHz min r2eff=%3.3f."%(min(r2eff_500))) 
7745              print(r2eff_500) 
7746              self.assertEqual(spin.r2[r20_key_500], min(r2eff_500)) 
7747              print("") 
7748   
7749          print("###########################################") 
7750          print("Trying GRID SEARCH for minimum R2eff values") 
7751   
7752          ### Test just the Grid search. 
7753          GRID_INC = 5 
7754   
7755          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7756   
7757          ### Then test the value.set function. 
7758          # Change pipe. 
7759          pipe_name_MODEL = "%s_%s_2"%(pipe_name, MODEL) 
7760          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7761          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7762   
7763          # Then select model. 
7764          self.interpreter.relax_disp.select_model(model=MODEL) 
7765   
7766          # Then set the standard parameter values. 
7767          for param in spin_params: 
7768              print("Setting standard parameter for param: %s"%param) 
7769              self.interpreter.value.set(param=param, index=None) 
7770   
7771          # Test result, for normal run. 
7772          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7773              # Print out. 
7774              print("r2_600=%2.2f r2_500=%2.2f pA=%2.2f, dw=%2.2f, kex=%2.2f, spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500], spin.pA, spin.dw, spin.kex, spin_id, resi, resn)) 
7775   
7776              # Testing the r2 values. 
7777              self.assertEqual(spin.r2[r20_key_600], 10.00) 
7778              self.assertEqual(spin.r2[r20_key_500], 10.00) 
7779              self.assertEqual(spin.pA, 0.9) 
7780              self.assertEqual(spin.dw, 1.0) 
7781              self.assertEqual(spin.kex, 1000.0) 
7782   
7783          print("###########################################") 
7784          print("Trying GRID SEARCH for standard R2eff values") 
7785   
7786          ### Test just the Grid search. 
7787          GRID_INC = 5 
7788   
7789          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7790   
7791          ### Run auto_analysis. 
7792          # The grid search size (the number of increments per dimension). 
7793          GRID_INC = 5 
7794   
7795          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7796          MC_NUM = 3 
7797   
7798          # Model selection technique. 
7799          MODSEL = 'AIC' 
7800   
7801          # Execute the auto-analysis (fast). 
7802          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7803          OPT_FUNC_TOL = 1e-1 
7804          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7805          OPT_MAX_ITERATIONS = 1000 
7806          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7807   
7808          # Run the analysis. 
7809          relax_disp.Relax_disp(pipe_name=pipe_name_r2eff, results_dir=ds.tmpdir, models=[MODEL], grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, set_grid_r20=True) 
7810   
7811   
7812 -    def test_show_apod_extract(self): 
7813          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod.""" 
7814   
7815          # The path to the data files. 
7816          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7817   
7818          # Define file name. 
7819          file_name = '128_0_FT.ft2' 
7820   
7821          # Call function. 
7822          get_output = show_apod_extract(file_name=file_name, dir=data_path) 
7823   
7824          # Define how output should look like. 
7825          # The output from showApod differs slightly according to NMRPipe version. But 'Noise Std Dev' is the same. 
7826          # Dont test lines which can differ. 
7827          show_apod_ver = [ 
7828              'REMARK Effect of Processing on Peak Parameters and Noise for %s'%(data_path+sep+file_name), 
7829              'REMARK Automated Noise Std Dev in Processed Data: 8583.41', 
7830              'REMARK Noise Std Dev Before Processing H1 and N15: 60.6558', 
7831              '', 
7832              'VARS   AXIS LABEL  TSIZE FSIZE LW_ADJ LW_FINAL HI_FACTOR VOL_FACTOR SIGMA_FACTOR', 
7833              'FORMAT %s   %-8s   %4d   %4d   %7.4f  %7.4f    %.4e      %.4e       %.4e'] 
7834              #'', 
7835              #'       X    H1       800  2048 0.8107 3.7310   4.9903e-03 9.8043e-04 5.2684e-02', 
7836              #'       Y    N15      128   256 0.7303 3.0331   3.1260e-02 7.8434e-03 1.3413e-01'] 
7837   
7838          for i, line in enumerate(show_apod_ver): 
7839              line_ver = get_output[i] 
7840   
7841              print(line) 
7842              if line[:50] == 'REMARK Noise Std Dev Before Processing H1 and N15:': 
7843                  continue 
7844              # Make the string test 
7845              self.assertEqual(line, line_ver) 
7846   
7847   
7848 -    def test_show_apod_rmsd(self): 
7849          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod.""" 
7850   
7851          # The path to the data files. 
7852          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7853   
7854          # Define file name. 
7855          file_name = '128_0_FT.ft2' 
7856   
7857          # Call function. 
7858          rmsd = show_apod_rmsd(file_name=file_name, dir=data_path) 
7859   
7860          # Assert. 
7861          self.assertEqual(rmsd, 8583.41) 
7862   
7863   
7864 -    def test_show_apod_rmsd_dir_to_files(self): 
7865          """Test searching for all NMRPipe spectrum files in dir, call showApod, and write to files.""" 
7866   
7867          # The path to the data files. 
7868          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7869   
7870          # Call function, and get all file names. 
7871          wfile_paths = show_apod_rmsd_dir_to_files(file_ext='.ft2', dir=data_path, outdir=self.tmpdir) 
7872   
7873          # Loop over file_paths. 
7874          for wfile_path in wfile_paths: 
7875              # Open the file. 
7876              get_data = extract_data(file=wfile_path) 
7877   
7878              # Extract line 0, column 0. 
7879              test = float(get_data[0][0]) 
7880   
7881              # Assert. 
7882              self.assertEqual(test, 8583.41) 
7883   
7884   
7885 -    def test_show_apod_rmsd_to_file(self): 
7886          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod, and write to file.""" 
7887   
7888          # The path to the data files. 
7889          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7890   
7891          # Define file name. 
7892          file_name = '128_0_FT.ft2' 
7893   
7894          # Call function, and get file name. 
7895          wfile_path = show_apod_rmsd_to_file(file_name=file_name, dir=data_path, outdir=self.tmpdir) 
7896   
7897          # Open the file. 
7898          get_data = extract_data(file=wfile_path) 
7899   
7900          # Extract line 0, column 0. 
7901          test = float(get_data[0][0]) 
7902   
7903          # Assert. 
7904          self.assertEqual(test, 8583.41) 
7905   
7906   
7907 -    def test_sod1wt_t25_bug_21954_order_error_analysis(self): 
7908          """Error analysis of SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
7909   
7910          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7911          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7912   
7913          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7914          Data is for experiment at 25 degree Celcius. 
7915   
7916          bug #21954 U{https://gna.org/bugs/index.php?21954}: Order of spectrum.error_analysis is important. 
7917          """ 
7918   
7919          # Base data setup. 
7920          pipe_name = 'base pipe' 
7921          pipe_type = 'relax_disp' 
7922          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7923          select_spin_index = list(range(0, 1)) 
7924          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7925   
7926          # Define replicated 
7927          repl_A = ['Z_A1', 'Z_A15'] 
7928          repl_B = ['Z_B1', 'Z_B18'] 
7929   
7930          # Loop over spectrum ID, and sort them 
7931          spectrum_ids_A = [] 
7932          spectrum_ids_B = [] 
7933          for spectrum_id in cdp.spectrum_ids: 
7934              if "A" in spectrum_id: 
7935                  spectrum_ids_A.append(spectrum_id) 
7936              elif "B" in spectrum_id: 
7937                  spectrum_ids_B.append(spectrum_id) 
7938   
7939          # To clean up old error analysis, delete attributes 
7940          delattr(cdp, "var_I") 
7941          delattr(cdp, "sigma_I") 
7942   
7943          # Perform error analysis 
7944          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_A) 
7945          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_B) 
7946   
7947          # Loop over spins, save errors to list 
7948          Errors_A_B = [] 
7949          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7950              A_err = spin.peak_intensity_err[spectrum_ids_A[0]] 
7951              B_err = spin.peak_intensity_err[spectrum_ids_B[0]] 
7952              Errors_A_B.append([A_err, B_err]) 
7953   
7954          # To clean up old error analysis, delete attributes 
7955          delattr(cdp, "var_I") 
7956          delattr(cdp, "sigma_I") 
7957   
7958          # Perform error analysis. Order is important 
7959          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_B) 
7960          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_A) 
7961   
7962          # Loop over spins, save errors to list 
7963          Errors_B_A = [] 
7964          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7965              A_err = spin.peak_intensity_err[spectrum_ids_A[0]] 
7966              B_err = spin.peak_intensity_err[spectrum_ids_B[0]] 
7967              Errors_B_A.append([A_err, B_err]) 
7968   
7969          # Make test for order of error 
7970          for i in range(len(Errors_A_B)): 
7971              Error_A_B = Errors_A_B[i] 
7972              Error_B_A = Errors_B_A[i] 
7973              self.assertAlmostEqual(Error_A_B[0], Error_B_A[0], 4) 
7974              self.assertAlmostEqual(Error_A_B[1], Error_B_A[1], 4) 
7975   
7976          # Make further tests for fixed values 
7977          std_A = math.sqrt((cdp.var_I[repl_A[0]] + cdp.var_I[repl_A[1]])/2) 
7978          std_A_fix = 2785.7263335738567 
7979   
7980          for id_A in spectrum_ids_A: 
7981              self.assertEqual(cdp.sigma_I[id_A], std_A) 
7982              self.assertAlmostEqual(cdp.sigma_I[id_A], std_A_fix, 7) 
7983   
7984          std_B = math.sqrt((cdp.var_I[repl_B[0]] + cdp.var_I[repl_B[1]])/2) 
7985          std_B_fix = 4967.3772030667988 
7986   
7987          for id_B in spectrum_ids_B: 
7988              self.assertEqual(cdp.sigma_I[id_B], std_B) 
7989              self.assertAlmostEqual(cdp.sigma_I[id_B], std_B_fix, 7) 
7990   
7991   
7992 -    def test_sod1wt_t25_to_cr72(self): 
7993          """Optimisation of SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
7994   
7995          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7996          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7997   
7998          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7999          Data is for experiment at 25 degree Celcius. 
8000          """ 
8001   
8002          # Base data setup. 
8003          pipe_name = 'base pipe' 
8004          pipe_type = 'relax_disp' 
8005          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
8006          select_spin_index = list(range(0, 2)) 
8007          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
8008   
8009          # Generate r20 key. 
8010          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
8011          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
8012   
8013          ## Now prepare for MODEL calculation. 
8014          MODEL = "CR72" 
8015   
8016          # Change pipe. 
8017          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
8018          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
8019          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
8020   
8021          # Then select model. 
8022          self.interpreter.relax_disp.select_model(model=MODEL) 
8023   
8024          # GRID inc of 7 was found to be appropriate not to find pA = 0.5. 
8025          GRID_INC = 7 
8026   
8027          # Store grid and minimisations results. 
8028          grid_results = [] 
8029          mini_results = [] 
8030          clust_results = [] 
8031   
8032          # Set the R20 parameters in the default grid search using the minimum R2eff value. 
8033          self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
8034   
8035          # Deselect insignificant spins. 
8036          self.interpreter.relax_disp.insignificance(level=1.0) 
8037   
8038          # Perform Grid Search. 
8039          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
8040   
8041          # Store result. 
8042          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8043              # Store grid results. 
8044              grid_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
8045   
8046          ## Now do minimisation. 
8047          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
8048          set_func_tol = 1e-9 
8049          set_max_iter = 100000 
8050          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
8051   
8052          # Store result. 
8053          pA_values = [] 
8054          kex_values = [] 
8055          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8056              # Store minimisation results. 
8057              mini_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
8058   
8059              # Store pA values. 
8060              pA_values.append(spin.pA) 
8061   
8062              # Store kex values. 
8063              kex_values.append(spin.kex) 
8064   
8065          print("\n# Now print before and after minimisation.\n") 
8066   
8067          # Print results. 
8068          for i in range(len(grid_results)): 
8069              # Get values. 
8070              g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
8071              m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
8072   
8073              print("GRID r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
8074              print("MIN  r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
8075   
8076          ## Prepare for clustering 
8077          # Change pipe. 
8078          pipe_name_MODEL_CLUSTER = "%s_%s_Cluster"%(pipe_name, MODEL) 
8079          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL_CLUSTER) 
8080          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL_CLUSTER) 
8081   
8082          # Then select model. 
8083          self.interpreter.relax_disp.select_model(model=MODEL) 
8084   
8085          # Define cluster id. 
8086          cluster_id = 'clust' 
8087   
8088          # Loop over spins to cluster them. 
8089          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8090              self.interpreter.relax_disp.cluster(cluster_id, spin_id) 
8091   
8092          # Copy over values. 
8093          self.interpreter.relax_disp.parameter_copy(pipe_from=pipe_name_MODEL, pipe_to=pipe_name_MODEL_CLUSTER) 
8094   
8095          # Test the median values is correct 
8096          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8097              print(pA_values) 
8098              # The the median pA value returned. 
8099              self.assertEqual(median(pA_values), spin.pA) 
8100   
8101              # The the median kex value returned. 
8102              self.assertEqual(median(kex_values), spin.kex) 
8103   
8104          ## Now do minimisation. 
8105          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
8106   
8107          # Store result. 
8108          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8109              # Store clust results. 
8110              clust_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
8111   
8112              # Store the outcome of the clustering minimisation. 
8113              clust_pA = spin.pA 
8114              clust_kex = spin.kex 
8115   
8116          print("\n# Now testing.\n") 
8117   
8118          # Define results 
8119          test_res = {} 
8120          test_res[':10@N'] = {} 
8121          test_res[':10@N']['r2600'] = 18.429755324773360 
8122          test_res[':10@N']['r2500'] = 16.981349161968630 
8123          test_res[':10@N']['dw'] = 2.700755859433969 
8124          test_res[':10@N']['pA'] = 0.971531659288657 
8125          test_res[':10@N']['kex'] = 3831.766337047963134 
8126          test_res[':11@N'] = {} 
8127          test_res[':11@N']['r2600'] = 18.193409421115213 
8128          test_res[':11@N']['r2500'] = 17.308838135567765 
8129          test_res[':11@N']['dw'] = 2.706650302761793 
8130          test_res[':11@N']['pA'] = 0.971531659288657 
8131          test_res[':11@N']['kex'] = 3831.766337047963134 
8132   
8133          # Then make tests. 
8134          for i in range(len(grid_results)): 
8135              # Get values. 
8136              g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
8137              m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
8138              c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn = clust_results[i] 
8139   
8140              print("%s GRID   r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
8141              print("%s MIN    r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
8142              print("%s Clust  r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn)) 
8143   
8144              # Make tests. 
8145              self.assertEqual(clust_pA, c_pA) 
8146              self.assertEqual(clust_kex, c_kex) 
8147   
8148              # Test values. 
8149              if c_spin_id in test_res: 
8150                  self.assertAlmostEqual(c_r2_600, test_res[c_spin_id]['r2600'], 4) 
8151                  self.assertAlmostEqual(c_r2_500, test_res[c_spin_id]['r2500'], 4) 
8152                  self.assertAlmostEqual(c_dw, test_res[c_spin_id]['dw'], 3) 
8153                  self.assertAlmostEqual(c_pA, test_res[c_spin_id]['pA'], 5) 
8154                  self.assertAlmostEqual(c_kex, test_res[c_spin_id]['kex'], 1) 
8155   
8156          # Save disp graph to temp. 
8157          #self.interpreter.relax_disp.plot_disp_curves(dir="~"+sep+"test", num_points=1000, extend=500.0, force=True). 
8158   
8159   
8160 -    def test_sod1wt_t25_to_sherekhan_input(self): 
8161          """Conversion of SOD1-WT CPMG R2eff values into input files for sherekhan. 
8162   
8163          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
8164          'SOD1-WT' CPMG data to the CR72 dispersion model. 
8165   
8166          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
8167          Data is for experiment at 25 degree Celcius. 
8168          """ 
8169   
8170          # Base data setup. 
8171          pipe_name = 'base pipe' 
8172          pipe_type = 'relax_disp' 
8173          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
8174          select_spin_index = list(range(0, 2)) 
8175          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
8176   
8177          # Generate r20 key. 
8178          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
8179          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
8180   
8181          # Cluster everything, to analyse together. 
8182          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":1-1000") 
8183   
8184          # Write input 
8185          self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None, dir=ds.tmpdir) 
8186   
8187          # Check the r2eff set files. 
8188          print("\nChecking the R2eff input set files.") 
8189          files = [[ds.tmpdir + sep + 'cluster1', 'sherekhan_frq1.in'], [ ds.tmpdir + sep + 'cluster1', 'sherekhan_frq2.in']] 
8190   
8191          # First check file exists 
8192          for dir, file in files: 
8193              print(dir+sep+file) 
8194              self.assert_(access(dir+sep+file, F_OK)) 
8195   
8196          # Define how files should look like 
8197          data_set_600 = [ 
8198               "60.8272464287\n", 
8199               "0.06\n", 
8200               "# nu_cpmg (Hz)       R2eff (rad/s)        Error               \n", 
8201               "# G10\n", 
8202               "              33.333       26.53556078711      0.5236104771163\n", 
8203               "              66.667       25.29735243318        0.48766574122\n", 
8204               "                 100       25.09470361403      0.4820438864671\n", 
8205               "             133.333       25.15603274331      0.4837377286085\n", 
8206               "             166.667       24.27213341753      0.4599457904395\n", 
8207               "                 200       24.00364120328      0.4529773198905\n", 
8208               "             266.667       24.03511395168      0.4537880662536\n", 
8209               "                 300       23.04761040024      0.4291039120557\n", 
8210               "             333.333       22.95530300787      0.4268745963972\n", 
8211               "                 400       23.06158810662      0.4294426293624\n", 
8212               "             466.667       22.26799054092      0.4106809618644\n", 
8213               "             533.333       21.99851418823      0.4045232104735\n", 
8214               "             666.667       21.19651570955      0.3868136173831\n", 
8215               "             833.333       20.30938498379      0.3682604887899\n", 
8216               "                1000       20.28273252609       0.367719392568\n", 
8217               "# D11\n", 
8218               "              33.333       24.76520269878      0.5026475808706\n", 
8219               "              66.667        24.8773107448      0.5058752916906\n", 
8220               "                 100       24.90357815239      0.5066348551479\n", 
8221               "             133.333        23.7782506151      0.4751950583865\n", 
8222               "             166.667       23.68548762076      0.4727017128631\n", 
8223               "                 200       23.58629651618      0.4700517377679\n", 
8224               "             266.667       23.47734671187      0.4671601744044\n", 
8225               "                 300       24.08647493772      0.4835855560598\n", 
8226               "             333.333       22.98314371029      0.4542918950801\n", 
8227               "                 400       22.80339361568      0.4497107885587\n", 
8228               "             466.667       22.91634335366      0.4525833037874\n", 
8229               "             533.333       22.59774140046      0.4445334311324\n", 
8230               "             666.667        20.9177750759      0.4046955726046\n", 
8231               "             833.333       20.71792550566      0.4002363835007\n", 
8232               "                1000       19.54080006349      0.3751112751853\n", 
8233          ] 
8234   
8235          # Check data_set_600 
8236          file = open(files[0][0]+sep+files[0][1]) 
8237          lines = file.readlines() 
8238          file.close() 
8239          self.assertEqual(len(data_set_600), len(lines)) 
8240          for i in range(len(data_set_600)): 
8241              # Make the string test 
8242              self.assertEqual(data_set_600[i], lines[i]) 
8243   
8244          # Define how files should look like 
8245          data_set_500 = [ 
8246               "50.6846152368\n", 
8247               "0.04\n", 
8248               "# nu_cpmg (Hz)       R2eff (rad/s)        Error               \n", 
8249               "# G10\n", 
8250               "                  50       22.28084307393      0.2944966344183\n", 
8251               "                 100       21.93494977761      0.2910362768307\n", 
8252               "                 150       21.09850032232       0.282892238351\n", 
8253               "                 200       20.86493960397      0.2806737853646\n", 
8254               "                 250       20.75287269752      0.2796178205016\n", 
8255               "                 300       20.25597152406      0.2750013546989\n", 
8256               "                 350       19.92172163467      0.2719555756504\n", 
8257               "                 400       19.97712052922       0.272457105051\n", 
8258               "                 450       19.46807010415      0.2678972122793\n", 
8259               "                 500       19.76875460947      0.2705774849203\n", 
8260               "                 550       19.39161367402      0.2672216964327\n", 
8261               "                 600       19.03949517697      0.2641417899694\n", 
8262               "                 650       19.12218812132      0.2648605059901\n", 
8263               "                 700       19.01037461457      0.2638893584683\n", 
8264               "                 800       18.83395162904      0.2623674321143\n", 
8265               "                 900       18.47529972436      0.2593123604687\n", 
8266               "                1000        18.5252023121      0.2597343394038\n", 
8267               "# D11\n", 
8268               "                  50       22.15403890237      0.3285588379827\n", 
8269               "                 100       21.80946781746      0.3247185598713\n", 
8270               "                 150       21.77715415505       0.324361526682\n", 
8271               "                 200       21.41647464235      0.3204122024881\n", 
8272               "                 250       21.17099940822      0.3177616325958\n", 
8273               "                 300       21.03740030577      0.3163316496664\n", 
8274               "                 350       20.95393648281      0.3154427665172\n", 
8275               "                 400       20.93311399332       0.315221543436\n", 
8276               "                 450       20.18219905222      0.3073848655291\n", 
8277               "                 500       19.93599065085      0.3048744697057\n", 
8278               "                 550       19.68475725452      0.3023424499113\n", 
8279               "                 600       19.33575433934      0.2988741928798\n", 
8280               "                 650       19.53915692194      0.3008886196853\n", 
8281               "                 700        19.2018754351      0.2975587767134\n", 
8282               "                 800       18.82360965368      0.2938866923878\n", 
8283               "                 900       18.71861761238      0.2928790380131\n", 
8284               "                1000       17.95878049287      0.2857341721151\n", 
8285          ] 
8286   
8287          # Check data_set_500 
8288          file = open(files[1][0]+sep+files[1][1]) 
8289          lines = file.readlines() 
8290          file.close() 
8291          self.assertEqual(len(data_set_500), len(lines)) 
8292          for i in range(len(data_set_500)): 
8293              # Make the string test 
8294              self.assertEqual(data_set_500[i], lines[i]) 
8295   
8296          # Test local dir tests. This will be turned off in system test. 
8297          turn_on_local_dir_test = False 
8298   
8299          if turn_on_local_dir_test: 
8300              ## Now check to local folder with None argument. 
8301              # Write input 
8302              self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None) 
8303   
8304              # Check the r2eff set files. 
8305              print("\nChecking the R2eff input set files.") 
8306              files = [[path.join(getcwd(), 'cluster1'), 'sherekhan_frq1.in'], [path.join(getcwd(), 'cluster1'), 'sherekhan_frq2.in']] 
8307   
8308              # First check file exists 
8309              for dir, file in files: 
8310                  print(dir+sep+file) 
8311                  self.assert_(access(dir+sep+file, F_OK)) 
8312   
8313              ## Now check to local folder with dir argument. 
8314              # Write input 
8315              set_dir = "Test_ShereKhan" 
8316              self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None, dir=set_dir) 
8317   
8318              # Check the r2eff set files. 
8319              print("\nChecking the R2eff input set files.") 
8320              files = [[path.join(getcwd(), set_dir, 'cluster1'), 'sherekhan_frq1.in'], [path.join(getcwd(), set_dir, 'cluster1'), 'sherekhan_frq2.in']] 
8321   
8322              # First check file exists 
8323              for dir, file in files: 
8324                  print(dir+sep+file) 
8325                  self.assert_(access(dir+sep+file, F_OK)) 
8326   
8327   
8328 -    def test_sprangers_data_to_mmq_cr72(self, model=None): 
8329          """Test the 'MMQ CR72' model fitting against Remco Sprangers' ClpP data. 
8330   
8331          This uses the data from Remco Sprangers' paper at http://dx.doi.org/10.1073/pnas.0507370102.  This is MMQ CPMG data with a fixed relaxation time period. 
8332          """ 
8333   
8334          # Reset. 
8335          self.interpreter.reset() 
8336   
8337          # Create the data pipe and load the base data. 
8338          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP' 
8339          self.interpreter.state.load(data_path+sep+'r2eff_values') 
8340   
8341          # The model data pipe. 
8342          model = 'MMQ CR72' 
8343          pipe_name = "%s - relax_disp" % model 
8344          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
8345          self.interpreter.pipe.switch(pipe_name=pipe_name) 
8346   
8347          # Set the model. 
8348          self.interpreter.relax_disp.select_model(model=model) 
8349   
8350          # Cluster everything. 
8351          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":135-137") 
8352   
8353          # Copy the data. 
8354          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
8355   
8356          # Alias the spins. 
8357          spin135S = cdp.mol[0].res[0].spin[0] 
8358          spin135F = cdp.mol[0].res[0].spin[1] 
8359          spin137S = cdp.mol[0].res[1].spin[0] 
8360          spin137F = cdp.mol[0].res[1].spin[1] 
8361   
8362          # The R20 keys. 
8363          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
8364          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8365   
8366          # Set the cluster specific parameters (only for the first spin). 
8367          spin135S.pA = 0.836591763632 
8368          spin135S.kex = 241.806525261 
8369   
8370          # Set the initial parameter values. 
8371          spin135S.r2 = {r20_key1: 28.2493431552, r20_key2: 31.7517334715} 
8372          spin135S.dw = 0.583003118785 
8373          spin135S.dwH = 0.0361441944301 
8374   
8375          spin135F.r2 = {r20_key1: 42.7201839991, r20_key2: 57.3178617389} 
8376          spin135F.dw = 0.805849745104 
8377          spin135F.dwH = 0.0215791945715 
8378   
8379          spin137S.r2 = {r20_key1: 26.0134115256, r20_key2: 30.575806934} 
8380          spin137S.dw = 0.688107568372 
8381          spin137S.dwH = 0.0344463604043 
8382   
8383          spin137F.r2 = {r20_key1: 46.6969397337, r20_key2: 58.602384101} 
8384          spin137F.dw = 0.94978299907 
8385          spin137F.dwH = 1.4818877939e-07 
8386   
8387          # Low precision optimisation. 
8388          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-10, max_iter=1000) 
8389   
8390          # Printout. 
8391          print("\n\nOptimised parameters:\n") 
8392          print("%-20s %-20s %-20s %-20s %-20s" % ("Parameter", "Value (:135@S)", "Value (:135@F)", "Value (:137@S)", "Value (:137@F)")) 
8393          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin135S.r2[r20_key1], spin135F.r2[r20_key1], spin137S.r2[r20_key1], spin137F.r2[r20_key1])) 
8394          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin135S.r2[r20_key2], spin135F.r2[r20_key2], spin137S.r2[r20_key2], spin137F.r2[r20_key2])) 
8395          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("pA", spin135S.pA, spin135F.pA, spin137S.pA, spin137F.pA)) 
8396          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dw", spin135S.dw, spin135F.dw, spin137S.dw, spin137F.dw)) 
8397          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dwH", spin135S.dwH, spin135F.dwH, spin137S.dwH, spin137F.dwH)) 
8398          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("kex", spin135S.kex, spin135F.kex, spin137S.kex, spin137F.kex)) 
8399          print("%-20s %20.15g %20.15g %20.15g %20.15g\n" % ("chi2", spin135S.chi2, spin135F.chi2, spin137S.chi2, spin137F.chi2)) 
8400          print("\n        # Set the cluster specific parameters (only for the first spin).") 
8401          print("        spin135S.pA = %s" % spin135S.pA) 
8402          print("        spin135S.kex = %s" % spin135S.kex) 
8403          print("\n        # Set the initial parameter values.") 
8404          print("        spin135S.r2 = {r20_key1: %s, r20_key2: %s}" % (spin135S.r2[r20_key1], spin135S.r2[r20_key2])) 
8405          print("        spin135S.dw = %s" % spin135S.dw) 
8406          print("        spin135S.dwH = %s" % spin135S.dwH) 
8407          print("\n        spin135F.r2 = {r20_key1: %s, r20_key2: %s}" % (spin135F.r2[r20_key1], spin135F.r2[r20_key2])) 
8408          print("        spin135F.dw = %s" % spin135F.dw) 
8409          print("        spin135F.dwH = %s" % spin135F.dwH) 
8410          print("\n        spin137S.r2 = {r20_key1: %s, r20_key2: %s}" % (spin137S.r2[r20_key1], spin137S.r2[r20_key2])) 
8411          print("        spin137S.dw = %s" % spin137S.dw) 
8412          print("        spin137S.dwH = %s" % spin137S.dwH) 
8413          print("\n        spin137F.r2 = {r20_key1: %s, r20_key2: %s}" % (spin137F.r2[r20_key1], spin137F.r2[r20_key2])) 
8414          print("        spin137F.dw = %s" % spin137F.dw) 
8415          print("        spin137F.dwH = %s" % spin137F.dwH) 
8416   
8417          # Checks for residue :135S. 
8418          self.assertAlmostEqual(spin135S.r2[r20_key1], 28.2493445347425, 4) 
8419          self.assertAlmostEqual(spin135S.r2[r20_key2], 31.7517352342937, 4) 
8420          self.assertAlmostEqual(spin135S.pA, 0.836591714049569, 4) 
8421          self.assertAlmostEqual(spin135S.dw, 0.583003004605869, 4) 
8422          self.assertAlmostEqual(spin135S.dwH, 0.0361441894065963, 4) 
8423          self.assertAlmostEqual(spin135S.kex/100, 241.806464344233/100, 4) 
8424          self.assertAlmostEqual(spin135S.chi2, 12.4224060116473, 4) 
8425   
8426          # Checks for residue :135F. 
8427          self.assertAlmostEqual(spin135F.r2[r20_key1], 42.7201844426839, 4) 
8428          self.assertAlmostEqual(spin135F.r2[r20_key2], 57.3178718548898, 4) 
8429          self.assertAlmostEqual(spin135F.pA, 0.836591714049569, 4) 
8430          self.assertAlmostEqual(spin135F.dw, 0.805849748711916, 4) 
8431          self.assertAlmostEqual(spin135F.dwH, 0.0215791669142752, 4) 
8432          self.assertAlmostEqual(spin135F.kex/100, 241.806464344233/100, 4) 
8433          self.assertAlmostEqual(spin135F.chi2, 12.4224060116473, 4) 
8434   
8435          # Checks for residue :137S. 
8436          self.assertAlmostEqual(spin137S.r2[r20_key1], 26.013412509919, 4) 
8437          self.assertAlmostEqual(spin137S.r2[r20_key2], 30.5758092335097, 4) 
8438          self.assertAlmostEqual(spin137S.pA, 0.836591714049569, 4) 
8439          self.assertAlmostEqual(spin137S.dw, 0.688107406812537, 4) 
8440          self.assertAlmostEqual(spin137S.dwH, 0.034446357344577, 4) 
8441          self.assertAlmostEqual(spin137S.kex/100, 241.806464344233/100, 4) 
8442          self.assertAlmostEqual(spin137S.chi2, 12.4224060116473, 4) 
8443   
8444          # Checks for residue :137F. 
8445          self.assertAlmostEqual(spin137F.r2[r20_key1], 46.696935090697, 4) 
8446          self.assertAlmostEqual(spin137F.r2[r20_key2], 58.6023842513446, 4) 
8447          self.assertAlmostEqual(spin137F.pA, 0.836591714049569, 4) 
8448          self.assertAlmostEqual(spin137F.dw, 0.94978325541294, 4) 
8449          self.assertAlmostEqual(spin137F.dwH, 1.5189362257653e-07, 4) 
8450          self.assertAlmostEqual(spin137F.kex/100, 241.806464344233/100, 4) 
8451          self.assertAlmostEqual(spin137F.chi2, 12.4224060116473, 4) 
8452   
8453   
8454 -    def test_sprangers_data_to_ns_mmq_2site(self, model=None): 
8455          """Test the 'NS MMQ 2-site' model fitting against Remco Sprangers' ClpP data. 
8456   
8457          This uses the data from Remco Sprangers' paper at http://dx.doi.org/10.1073/pnas.0507370102.  This is MQ CPMG data with a fixed relaxation time period. 
8458          """ 
8459   
8460          # Reset. 
8461          self.interpreter.reset() 
8462   
8463          # Create the data pipe and load the base data. 
8464          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP' 
8465          self.interpreter.state.load(data_path+sep+'r2eff_values') 
8466   
8467          # The model data pipe. 
8468          model = 'NS MMQ 2-site' 
8469          pipe_name = "%s - relax_disp" % model 
8470          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
8471          self.interpreter.pipe.switch(pipe_name=pipe_name) 
8472   
8473          # Set the model. 
8474          self.interpreter.relax_disp.select_model(model=model) 
8475   
8476          # Cluster everything. 
8477          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":135-137") 
8478   
8479          # Copy the data. 
8480          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
8481   
8482          # Alias the spins. 
8483          spin135S = cdp.mol[0].res[0].spin[0] 
8484          spin135F = cdp.mol[0].res[0].spin[1] 
8485          spin137S = cdp.mol[0].res[1].spin[0] 
8486          spin137F = cdp.mol[0].res[1].spin[1] 
8487   
8488          # The R20 keys. 
8489          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8490          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8491   
8492          # Set the cluster specific parameters (only for the first spin). 
8493          spin135S.pA = 0.847378444499757 
8494          spin135S.kex = 264.055604934724329 
8495   
8496          # Set the initial parameter values. 
8497          spin135S.r2 = {r20_key1: 30.315119723745390, r20_key2: 37.411874745645299} 
8498          spin135S.dw = 0.585574008745351 
8499          spin135S.dwH = 0.000000000000002 
8500   
8501          spin135F.r2 = {r20_key1: 41.440843383778287, r20_key2: 56.989726795397893} 
8502          spin135F.dw = 0.856699277665748 
8503          spin135F.dwH = 0.000000000582587 
8504   
8505          spin137S.r2 = {r20_key1: 23.051695938570266, r20_key2: 28.352806483953824} 
8506          spin137S.dw = 0.772904450844973 
8507          spin137S.dwH = 0.183351478512970 
8508   
8509          spin137F.r2 = {r20_key1: 44.702032074210429, r20_key2: 56.453146052685319} 
8510          spin137F.dw = 0.984568590342831 
8511          spin137F.dwH = 0.000000001993458 
8512   
8513          # Low precision optimisation. 
8514          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-5, grad_tol=None, max_iter=100, constraints=True, scaling=True, verbosity=1) 
8515   
8516          # Printout. 
8517          print("\n\nOptimised parameters:\n") 
8518          print("%-20s %-20s %-20s %-20s %-20s" % ("Parameter", "Value (:135@S)", "Value (:135@F)", "Value (:137@S)", "Value (:137@F)")) 
8519          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin135S.r2[r20_key1], spin135F.r2[r20_key1], spin137S.r2[r20_key1], spin137F.r2[r20_key1])) 
8520          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin135S.r2[r20_key2], spin135F.r2[r20_key2], spin137S.r2[r20_key2], spin137F.r2[r20_key2])) 
8521          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("pA", spin135S.pA, spin135F.pA, spin137S.pA, spin137F.pA)) 
8522          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dw", spin135S.dw, spin135F.dw, spin137S.dw, spin137F.dw)) 
8523          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dwH", spin135S.dwH, spin135F.dwH, spin137S.dwH, spin137F.dwH)) 
8524          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("kex", spin135S.kex, spin135F.kex, spin137S.kex, spin137F.kex)) 
8525          print("%-20s %20.15g %20.15g %20.15g %20.15g\n" % ("chi2", spin135S.chi2, spin135F.chi2, spin137S.chi2, spin137F.chi2)) 
8526   
8527          # FIXME: Remove this temporary return and properly check the results. 
8528          return 
8529   
8530          # Checks for residue :135S. 
8531          self.assertAlmostEqual(spin135S.r2[r20_key1], 30.3151197237454, 4) 
8532          self.assertAlmostEqual(spin135S.r2[r20_key2], 37.4118747456453, 4) 
8533          self.assertAlmostEqual(spin135S.pA, 0.847378444499757, 4) 
8534          self.assertAlmostEqual(spin135S.dw, 0.585574008745351, 4) 
8535          self.assertAlmostEqual(spin135S.dwH, 2e-15, 4) 
8536          self.assertAlmostEqual(spin135S.kex, 264.055604934724, 4) 
8537          self.assertAlmostEqual(spin135S.chi2, 13.859423588071, 1) 
8538   
8539          # Checks for residue :135F. 
8540          self.assertAlmostEqual(spin135F.r2[r20_key1], 41.4408433837783, 4) 
8541          self.assertAlmostEqual(spin135F.r2[r20_key2], 56.9897267953979, 4) 
8542          self.assertAlmostEqual(spin135F.pA, 0.847378444499757, 4) 
8543          self.assertAlmostEqual(spin135F.dw, 0.856699277665748, 4) 
8544          self.assertAlmostEqual(spin135F.dwH, 5.82587e-10, 4) 
8545          self.assertAlmostEqual(spin135F.kex, 264.055604934724, 4) 
8546          self.assertAlmostEqual(spin135F.chi2, 13.859423588071, 1) 
8547   
8548          # Checks for residue :137S. 
8549          self.assertAlmostEqual(spin137S.r2[r20_key1], 23.0516959385703, 4) 
8550          self.assertAlmostEqual(spin137S.r2[r20_key2], 28.3528064839538, 4) 
8551          self.assertAlmostEqual(spin137S.pA, 0.847378444499757, 4) 
8552          self.assertAlmostEqual(spin137S.dw, 0.772904450844973, 4) 
8553          self.assertAlmostEqual(spin137S.dwH, 0.18335147851297, 4) 
8554          self.assertAlmostEqual(spin137S.kex, 264.055604934724, 4) 
8555          self.assertAlmostEqual(spin137S.chi2, 13.859423588071, 1) 
8556   
8557          # Checks for residue :137F. 
8558          self.assertAlmostEqual(spin137F.r2[r20_key1], 44.7020320742104, 4) 
8559          self.assertAlmostEqual(spin137F.r2[r20_key2], 56.4531460526853, 4) 
8560          self.assertAlmostEqual(spin137F.pA, 0.847378444499757, 4) 
8561          self.assertAlmostEqual(spin137F.dw, 0.984568590342831, 4) 
8562          self.assertAlmostEqual(spin137F.dwH, 2.0931309e-09, 4) 
8563          self.assertAlmostEqual(spin137F.kex, 264.055604934724, 4) 
8564          self.assertAlmostEqual(spin137F.chi2, 13.859423588071, 1) 
8565   
8566   
8567 -    def test_tp02_data_to_ns_r1rho_2site(self, model=None): 
8568          """Test the relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data.""" 
8569   
8570          # Setup the data. 
8571          self.setup_tp02_data_to_ns_r1rho_2site() 
8572   
8573          # Alias the spins. 
8574          spin1 = cdp.mol[0].res[0].spin[0] 
8575          spin2 = cdp.mol[0].res[1].spin[0] 
8576   
8577          # The R20 keys. 
8578          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8579          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8580   
8581          # Checks for residue :1. 
8582          self.assertAlmostEqual(spin1.r2[r20_key1], 8.50207717367548, 4) 
8583          self.assertAlmostEqual(spin1.r2[r20_key2], 13.4680429589972, 4) 
8584          self.assertAlmostEqual(spin1.pA, 0.864523128842393, 4) 
8585          self.assertAlmostEqual(spin1.dw, 8.85204828994151, 4) 
8586          self.assertAlmostEqual(spin1.kex/1000, 1199.56359549637/1000, 4) 
8587          self.assertAlmostEqual(spin1.chi2, 2.99182130153514, 4) 
8588   
8589          # Checks for residue :2. 
8590          self.assertAlmostEqual(spin2.r2[r20_key1], 10.2099357790203, 4) 
8591          self.assertAlmostEqual(spin2.r2[r20_key2], 16.2137648697873, 4) 
8592          self.assertAlmostEqual(spin2.pA, 0.836488681031685, 4) 
8593          self.assertAlmostEqual(spin2.dw, 9.5505714779503, 4) 
8594          self.assertAlmostEqual(spin2.kex/1000, 1454.45726998929/1000, 4) 
8595          self.assertAlmostEqual(spin2.chi2, 0.000402231563481261, 4) 
8596   
8597   
8598 -    def test_tp02_data_to_ns_r1rho_2site_cluster(self, model=None): 
8599          """Test the relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data, when performing clustering.""" 
8600   
8601          # Setup the data. 
8602          self.setup_tp02_data_to_ns_r1rho_2site(clustering=True) 
8603   
8604          # Alias the spins. 
8605          spin1 = cdp.mol[0].res[0].spin[0] 
8606          spin2 = cdp.mol[0].res[1].spin[0] 
8607   
8608          # The R20 keys. 
8609          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8610          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8611   
8612          # Checks for residue :1. 
8613          self.assertAlmostEqual(spin1.r2[r20_key1], 8.48607207881462, 4) 
8614          self.assertAlmostEqual(spin1.r2[r20_key2], 13.4527609061722, 4) 
8615          self.assertAlmostEqual(spin1.pA, 0.863093838784425, 4) 
8616          self.assertAlmostEqual(spin1.dw, 8.86218096536618, 4) 
8617          self.assertAlmostEqual(spin1.kex/1000, 1186.22749648299/1000, 4) 
8618          self.assertAlmostEqual(spin1.chi2, 3.09500996065247, 4) 
8619   
8620          # Checks for residue :2. 
8621          self.assertAlmostEqual(spin2.r2[r20_key1], 10.4577906018883, 4) 
8622          self.assertAlmostEqual(spin2.r2[r20_key2], 16.4455550953792, 4) 
8623          self.assertAlmostEqual(spin2.pA, 0.863093838784425, 4) 
8624          self.assertAlmostEqual(spin2.dw, 11.5841168862587, 4) 
8625          self.assertAlmostEqual(spin2.kex/1000, 1186.22749648299/1000, 4) 
8626          self.assertAlmostEqual(spin2.chi2, 3.09500996065247, 4) 
8627   
8628   
8629 -    def test_tp02_data_to_mp05(self): 
8630          """Test the dispersion 'MP05' model fitting against the 'TP02' test data.""" 
8631   
8632          # Fixed time variable and the models. 
8633          ds.fixed = True 
8634          ds.models = ['R2eff', 'MP05'] 
8635   
8636          # Execute the script. 
8637          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8638   
8639          # Switch back to the data pipe for the optimisation. 
8640          self.interpreter.pipe.switch('MP05 - relax_disp') 
8641   
8642          # The equivalent MP05 parameters. 
8643          r1rho_prime = [[10.0058086343329, 15.005806870124], [12.0766320470785, 18.0767503536277]] 
8644          pA = [0.775055484521586, 0.500000000036595] 
8645          kex = [1235.20361276079, 2378.31403454691] 
8646          delta_omega = [7.08194146569694, 5.4083562844306] 
8647          chi2 = [0.0370400968727768, 0.182141732163934] 
8648   
8649          # Alias the spins. 
8650          spin1 = cdp.mol[0].res[0].spin[0] 
8651          spin2 = cdp.mol[0].res[1].spin[0] 
8652   
8653          # The R20 keys. 
8654          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8655          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8656   
8657          # Printout. 
8658          print("\n\nOptimised parameters:\n") 
8659          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
8660          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
8661          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
8662          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
8663          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
8664          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
8665          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
8666   
8667          # Check each spin. 
8668          spin_index = 0 
8669          for spin, spin_id in spin_loop(return_id=True): 
8670              # Printout. 
8671              print("\nSpin %s." % spin_id) 
8672   
8673              # Check the fitted parameters. 
8674              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8675              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8676              self.assertAlmostEqual(spin.pA, pA[spin_index], 3) 
8677              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8678              self.assertAlmostEqual(spin.kex/1000.0, kex[spin_index]/1000.0, 3) 
8679              self.assertAlmostEqual(spin.chi2, chi2[spin_index], 3) 
8680   
8681              # Increment the spin index. 
8682              spin_index += 1 
8683   
8684   
8685 -    def test_tp02_data_to_tap03(self): 
8686          """Test the dispersion 'TAP03' model fitting against the 'TP02' test data.""" 
8687   
8688          # Fixed time variable and the models. 
8689          ds.fixed = True 
8690          ds.models = ['R2eff', 'TAP03'] 
8691   
8692          # Execute the script. 
8693          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8694   
8695          # Switch back to the data pipe for the optimisation. 
8696          self.interpreter.pipe.switch('TAP03 - relax_disp') 
8697   
8698          # The equivalent TAP03 parameters. 
8699          r1rho_prime = [[10.0058156589442, 15.005818505006], [12.0766046472748, 18.076648462452]] 
8700          pA = [0.775042569092891, 0.500000000229685] 
8701          kex = [1235.20852748765, 2379.47085580169] 
8702          delta_omega = [7.08176806468445, 5.40708372863538] 
8703          chi2 = [0.0371366837083293, 0.182212857256044] 
8704   
8705          # Alias the spins. 
8706          spin1 = cdp.mol[0].res[0].spin[0] 
8707          spin2 = cdp.mol[0].res[1].spin[0] 
8708   
8709          # The R20 keys. 
8710          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8711          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8712   
8713          # Printout. 
8714          print("\n\nOptimised parameters:\n") 
8715          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
8716          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
8717          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
8718          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
8719          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
8720          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
8721          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
8722   
8723          # Switch to the 'MP05' model data pipe, then check for each spin. 
8724          self.interpreter.pipe.switch('TAP03 - relax_disp') 
8725          spin_index = 0 
8726          for spin, spin_id in spin_loop(return_id=True): 
8727              # Printout. 
8728              print("\nSpin %s." % spin_id) 
8729   
8730              # Check the fitted parameters. 
8731              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8732              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8733              self.assertAlmostEqual(spin.pA, pA[spin_index], 3) 
8734              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8735              self.assertAlmostEqual(spin.kex/1000.0, kex[spin_index]/1000.0, 3) 
8736              self.assertAlmostEqual(spin.chi2, chi2[spin_index], 3) 
8737   
8738              # Increment the spin index. 
8739              spin_index += 1 
8740   
8741   
8742 -    def test_task_7882_monte_carlo_std_residual(self): 
8743          """Implementation of Task #7882 U{https://gna.org/task/?7882}: Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals""" 
8744   
8745          # First check that results are stored with minimisation, to make sure that Sum of Squares are stored (Chi2 without weighting) and degrees of freedom (dof) is stored. 
8746   
8747          # Load the results file from a clustered minimisation. 
8748          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'error_testing'+sep+'task_7882' 
8749          self.interpreter.results.read(file_name) 
8750   
8751          # Get the spins, which was used for clustering. 
8752          spins_cluster = cdp.clustering['sel'] 
8753          spins_free = cdp.clustering['free spins'] 
8754   
8755          # For sanity check, calculate degree of freedom. 
8756          cur_spin_id = spins_cluster[0] 
8757          cur_spin = return_spin(cur_spin_id) 
8758   
8759          # Calculate total number of datapoins. 
8760          N = len(spins_cluster) 
8761          N_dp = N * len(cur_spin.r2eff) 
8762   
8763          # Calculate number of paramaters. For CR72, there is R2 per spectrometer field, individual dw, and shared kex and pA. 
8764          N_par = cdp.spectrometer_frq_count * N + N + 1 + 1 
8765          dof = N_dp - N_par 
8766   
8767          # Sanity check of parameters. 
8768          print(N_par, N_dp) 
8769   
8770          # Number of MC 
8771          mc_nr = 3 
8772   
8773          # Setup MC for errors generated from the distribution described by chi2 and degrees of freedom from best fit. 
8774          self.interpreter.monte_carlo.setup(number=mc_nr) 
8775   
8776          # Create data. 
8777          self.interpreter.monte_carlo.create_data(distribution="red_chi2") 
8778   
8779          # Setup MC again. 
8780          self.interpreter.monte_carlo.setup(number=mc_nr) 
8781   
8782          # Create data, and set the fixed error value, without setting the correct distribution. 
8783          self.assertRaises(RelaxError, self.interpreter.monte_carlo.create_data, fixed_error=1.) 
8784   
8785          # Setup MC again. 
8786          self.interpreter.monte_carlo.setup(number=mc_nr) 
8787   
8788          # Create data, with fixed error distribution, but not setting the error value. 
8789          self.assertRaises(RelaxError, self.interpreter.monte_carlo.create_data, distribution="fixed") 
8790   
8791          # Setup MC again. 
8792          self.interpreter.monte_carlo.create_data(distribution="fixed", fixed_error=1.) 
8793   
8794          # Now select the R2eff model, and try again. Expect raising an error. 
8795          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
8796   
8797          # Setup MC again. 
8798          self.interpreter.monte_carlo.setup(number=mc_nr) 
8799   
8800          # Create data, and assert failure. 
8801          self.assertRaises(RelaxError, self.interpreter.monte_carlo.create_data, distribution="red_chi2") 
8802          self.assertRaises(RelaxError, self.interpreter.monte_carlo.create_data, method="direct", distribution="red_chi2") 
8803   
8804   
8805 -    def x_test_task_7882_kex_conf(self): 
8806          """Test related to Task #7882 U{https://gna.org/task/?7882}: Try making a confidence interval of kex. 
8807          According to the regression book of Graphpad: U{http://www.graphpad.com/faq/file/Prism4RegressionBook.pdf}. 
8808          Page 109-111. 
8809          """ 
8810   
8811          # Load the results file from a clustered minimisation. 
8812          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'error_testing'+sep+'task_7882' 
8813          self.interpreter.results.read(file_name) 
8814   
8815          # Get the spins, which was used for clustering. 
8816          spins_cluster = cdp.clustering['sel'] 
8817          spins_free = cdp.clustering['free spins'] 
8818   
8819          # For sanity check, calculate degree of freedom. 
8820          cur_spin_id = spins_cluster[0] 
8821          cur_spin = return_spin(cur_spin_id) 
8822   
8823          # Calculate total number of datapoins. 
8824          Ns = len(spins_cluster) 
8825          N_dp = Ns * len(cur_spin.r2eff) 
8826   
8827          # Calculate number of paramaters. For CR72, there is R2 per spectrometer field, individual dw, and shared kex and pA. 
8828          N_par = cdp.spectrometer_frq_count * Ns + Ns + 1 + 1 
8829          dof_fit = N_dp - N_par 
8830   
8831          # Assert values. 
8832          self.assertEqual(Ns, 61) 
8833          self.assertEqual(N_dp, 1952) 
8834          self.assertEqual(N_par, 185) 
8835   
8836          # Confidence interval of kex. 
8837          # The number of parameters to check is kex = 1. 
8838          P = 1 
8839          # Number of datapoints 
8840          N = N_dp 
8841          # The degrees of freedom for this confidence interval 
8842          dof_conf = N - P 
8843   
8844          # The critical value of the F distribution with p-value of 0.05 for 95% confidence. 
8845          # Can be calculated with microsoft excel: 
8846          # F=FINV(0,05; P; dof_conf), F=FINV(0,05; P; dof_conf), F=FINV(0,05; 1; 1951)=3,846229551 
8847          # Can also be calculated with: import scipy.stats; scipy.stats.f.isf(0.05, 1, 1951)=3.8462295505435562 
8848          F = 3.8462295505435562 
8849          # Then calculate the scaling of chi2, which is the weighted sum of squares of best fit. 
8850          scale = F*P/dof_conf +1 
8851   
8852          # Get the sum of best fit. 
8853          SSbest_fit = cur_spin.chi2 
8854          SSbest_kex = cur_spin.kex 
8855   
8856          # Get the scaled sum of best fit 
8857          SSall_fixed = SSbest_fit * scale 
8858   
8859          print(SSbest_fit, scale, SSall_fixed) 
8860   
8861          # Now generate a list of kex values to try. 
8862          kex_cur = cur_spin.kex 
8863          kex_list = linspace(kex_cur - 1500, kex_cur + 3000, 200) 
8864   
8865          chi2_list = [] 
8866   
8867          for kex in kex_list: 
8868              self.interpreter.value.set(val=kex, param='kex') 
8869   
8870              # Calculate the chi2 values. 
8871              self.interpreter.minimise.calculate(verbosity=0) 
8872   
8873              # Get the chi2 value 
8874              chi2_cur = cur_spin.chi2 
8875              print("kex=%3.2f, chi2=%3.2f"%(kex, chi2_cur), chi2_cur<SSall_fixed) 
8876   
8877              # Add to list 
8878              chi2_list.append(chi2_cur) 
8879   
8880          # Now make to numpy array. 
8881          chi2_list = asarray(chi2_list) 
8882   
8883          # Now make a selection mask based on the criteria. 
8884          sel_mask = chi2_list < SSall_fixed 
8885   
8886          # Select values of kex, and chi2_list 
8887          kex_sel = kex_list[sel_mask] 
8888          chi2_sel = chi2_list[sel_mask] 
8889   
8890          # Now make plot 
8891          print(SSbest_kex, SSbest_fit, SSall_fixed) 
8892          print(kex_sel) 
8893          print(chi2_sel) 
8894   
8895          if True: 
8896              import matplotlib.pyplot as plt 
8897   
8898              plt.plot(kex_sel, chi2_sel, "bo") 
8899              plt.plot(SSbest_kex, SSbest_fit, "g*") 
8900              plt.show() 
8901   
8902   
8903 -    def test_tp02_data_to_tp02(self): 
8904          """Test the relaxation dispersion 'TP02' model curve fitting to fixed time synthetic data.""" 
8905   
8906          # Fixed time variable. 
8907          ds.fixed = True 
8908   
8909          # Execute the script. 
8910          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8911   
8912          # The original parameters. 
8913          r1rho_prime = [[10.0, 15.0], [12.0, 18.0]] 
8914          pA = 0.7654321 
8915          kex = 1234.56789 
8916          delta_omega = [7.0, 9.0] 
8917   
8918          # The R20 keys. 
8919          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8920          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8921   
8922          # Switch to the 'TP02' model data pipe, then check for each spin. 
8923          self.interpreter.pipe.switch('TP02 - relax_disp') 
8924          spin_index = 0 
8925          for spin, spin_id in spin_loop(return_id=True): 
8926              # Printout. 
8927              print("\nSpin %s." % spin_id) 
8928   
8929              # Check the fitted parameters. 
8930              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8931              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8932              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8933              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 3) 
8934   
8935              # Increment the spin index. 
8936              spin_index += 1 
8937   
8938   
8939 -    def test_value_write_calc_rotating_frame_params_int(self): 
8940          """System test of the value.write function to write intensities for an R1rho setup. 
8941          This system test is to make sure, that modifying the API for special parameters theta and w_eff does not alter the functionality value.write. 
8942   
8943          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8944          """ 
8945   
8946          # Load the state. 
8947          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8948          self.interpreter.state.load(statefile, force=True) 
8949   
8950          # Set filepaths. 
8951          int_filepath = ds.tmpdir+sep+'int.out' 
8952   
8953          # Write out the intensity parameter file. 
8954          # The writing out of intensity file is to make sure the API function retains its function after modification for special parameters. 
8955          self.interpreter.value.write(param='peak_intensity', file='int.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8956   
8957          # Test the file exists. 
8958          self.assert_(access(int_filepath, F_OK)) 
8959   
8960          # Open the files for testing. 
8961          int_file = open(int_filepath, 'r') 
8962   
8963          # Loop over the intensity file to test values. 
8964          for line in int_file: 
8965              # Skip lines starting with #. 
8966              if line[0] == "#": 
8967                  continue 
8968   
8969              # Split the line 
8970              linesplit = line.split() 
8971   
8972              # Assume values 
8973              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8974                  self.assertEqual(linesplit[5], "115571.4") 
8975              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8976                  self.assertEqual(linesplit[5], "68377.52") 
8977              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8978                  self.assertEqual(linesplit[5], "9141.689") 
8979              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8980                  self.assertEqual(linesplit[5], "29123.77") 
8981              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8982                  self.assertEqual(linesplit[5], "58914.94") 
8983   
8984          # Close files 
8985          int_file.close() 
8986   
8987   
8988 -    def test_value_write_calc_rotating_frame_params_theta(self): 
8989          """System test of the value.write function to write return values of theta from calc_rotating_frame_params() function for an R1rho setup. 
8990   
8991          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8992          """ 
8993   
8994          # Load the state. 
8995          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8996          self.interpreter.state.load(statefile, force=True) 
8997   
8998          # Set filepaths. 
8999          theta_filepath = ds.tmpdir+sep+'theta.out' 
9000   
9001          # Write out the theta parameter file. 
9002          self.interpreter.value.write(param='theta', file='theta.out', dir=ds.tmpdir, scaling=1.0, force=True) 
9003   
9004          # Test the file exists. 
9005          self.assert_(access(theta_filepath, F_OK)) 
9006   
9007          # Open the files for testing. 
9008          theta_file = open(theta_filepath, 'r') 
9009   
9010          # Loop over the theta file to test values. 
9011          for line in theta_file: 
9012              # Skip lines starting with #. 
9013              if line[0] == "#": 
9014                  continue 
9015              # Print lines, not including newline character. 
9016              print(line[:-1]) 
9017   
9018              # Split the line 
9019              linesplit = line.split() 
9020   
9021              # Assume values 
9022              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
9023                  self.assertNotEqual(linesplit[5], "None") 
9024              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
9025                  self.assertNotEqual(linesplit[5], "None") 
9026              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
9027                  self.assertNotEqual(linesplit[5], "None") 
9028              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
9029                  self.assertNotEqual(linesplit[5], "None") 
9030              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
9031                  self.assertNotEqual(linesplit[5], "None") 
9032   
9033          # Close files 
9034          theta_file.close() 
9035   
9036   
9037 -    def test_value_write_calc_rotating_frame_params_w_eff(self): 
9038          """System test of the value.write function to write return values of w_eff from calc_rotating_frame_params() function for an R1rho setup. 
9039   
9040          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
9041          """ 
9042   
9043          # Load the state. 
9044          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
9045          self.interpreter.state.load(statefile, force=True) 
9046   
9047          # Set filepaths. 
9048          w_eff_filepath = ds.tmpdir+sep+'w_eff.out' 
9049   
9050          # Write out the w_eff parameter file. 
9051          self.interpreter.value.write(param='w_eff', file='w_eff.out', dir=ds.tmpdir, scaling=1.0, force=True) 
9052   
9053          # Test the file exists. 
9054          self.assert_(access(w_eff_filepath, F_OK)) 
9055   
9056          # Open the files for testing. 
9057          w_eff_file = open(w_eff_filepath, 'r') 
9058   
9059          # Loop over the w_eff file to test values. 
9060          for line in w_eff_file: 
9061              # Skip lines starting with #. 
9062              if line[0] == "#": 
9063                  continue 
9064              # Print lines, not including newline character. 
9065              print(line[:-1]) 
9066   
9067              # Split the line 
9068              linesplit = line.split() 
9069   
9070              # Assume values 
9071              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
9072                  self.assertNotEqual(linesplit[5], "None") 
9073              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
9074                  self.assertNotEqual(linesplit[5], "None") 
9075              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
9076                  self.assertNotEqual(linesplit[5], "None") 
9077              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
9078                  self.assertNotEqual(linesplit[5], "None") 
9079              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
9080                  self.assertNotEqual(linesplit[5], "None") 
9081   
9082          # Close files 
9083          w_eff_file.close() 
9084   
9085   
9086 -    def test_value_write_calc_rotating_frame_params_auto_analysis(self): 
9087          """System test of the auto_analysis value.write function to write theta and w_eff values for an R1rho setup. 
9088   
9089          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
9090          """ 
9091   
9092          # Load the state. 
9093          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344.bz2' 
9094          self.interpreter.state.load(statefile, force=True) 
9095   
9096          # Set pipe name, bundle and type. 
9097          pipe_name = 'base pipe' 
9098          pipe_bundle = 'relax_disp' 
9099          pipe_type = 'relax_disp' 
9100   
9101          # The path to the data files. 
9102          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
9103   
9104          # Deselect all spins 
9105          self.interpreter.deselect.all() 
9106   
9107          # Specify spins to be selected. 
9108          select_spin_ids = [ 
9109          ":13@N", 
9110          ":15@N", 
9111          ":16@N", 
9112          ":25@N", 
9113          ":26@N", 
9114          ":28@N", 
9115          ":39@N", 
9116          ":40@N", 
9117          ":41@N", 
9118          ":43@N", 
9119          ":44@N", 
9120          ":45@N", 
9121          ":49@N", 
9122          ":52@N", 
9123          ":53@N"] 
9124   
9125          # Reverse the selection for the spins. 
9126          for curspin in select_spin_ids: 
9127              print("Selecting spin %s"%curspin) 
9128              self.interpreter.deselect.reverse(spin_id=curspin) 
9129   
9130          # Read the R1 data 
9131          self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
9132   
9133          # The dispersion models. 
9134          MODELS = ['R2eff'] 
9135   
9136          # The grid search size (the number of increments per dimension). 
9137          GRID_INC = 4 
9138   
9139          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
9140          MC_NUM = 3 
9141   
9142          # Model selection technique. 
9143          MODSEL = 'AIC' 
9144   
9145          # Execute the auto-analysis (fast). 
9146          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
9147          OPT_FUNC_TOL = 1e-1 
9148          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
9149          OPT_MAX_ITERATIONS = 1000 
9150          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
9151   
9152          # Run the analysis. 
9153          relax_disp.Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, results_dir=ds.tmpdir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
9154   
9155          ## Check for file creation 
9156          # Set filepaths. 
9157          theta_filepath = ds.tmpdir+sep+MODELS[0]+sep+'theta.out' 
9158          w_eff_filepath = ds.tmpdir+sep+MODELS[0]+sep+'w_eff.out' 
9159   
9160          # Test the files exists. 
9161          self.assert_(access(theta_filepath, F_OK)) 
9162          self.assert_(access(w_eff_filepath, F_OK)) 
9163   
9164          # Open the files for testing. 
9165          theta_file = open(theta_filepath, 'r') 
9166          theta_result = [ 
9167              "# Parameter description:  Rotating frame tilt angle : ( theta = arctan(w_1 / Omega) ) (rad).\n", 
9168              "#\n", 
9169              "# mol_name    res_num    res_name    spin_num    spin_name    r1rho_799.77739910_118.078_1341.110    sd(r1rho_799.77739910_118.078_1341.110)    r1rho_799.77739910_118.078_1648.500    sd(r1rho_799.77739910_118.078_1648.500)    r1rho_799.77739910_118.078_431.000    sd(r1rho_799.77739910_118.078_431.000)    r1rho_799.77739910_118.078_651.200    sd(r1rho_799.77739910_118.078_651.200)    r1rho_799.77739910_118.078_800.500    sd(r1rho_799.77739910_118.078_800.500)    r1rho_799.77739910_118.078_984.000    sd(r1rho_799.77739910_118.078_984.000)    r1rho_799.77739910_124.247_1341.110    sd(r1rho_799.77739910_124.247_1341.110)    r1rho_799.77739910_130.416_1341.110    sd(r1rho_799.77739910_130.416_1341.110)    r1rho_799.77739910_130.416_1648.500    sd(r1rho_799.77739910_130.416_1648.500)    r1rho_799.77739910_130.416_800.500    sd(r1rho_799.77739910_130.416_800.500)    r1rho_799.77739910_142.754_1341.110    sd(r1rho_799.77739910_142.754_1341.110)    r1rho_799.77739910_142.754_800.500    sd(r1rho_799.77739910_142.754_800.500)    r1rho_799.77739910_179.768_1341.110    sd(r1rho_799.77739910_179.768_1341.110)    r1rho_799.77739910_241.459_1341.110    sd(r1rho_799.77739910_241.459_1341.110)    \n", 
9170              "None          5          I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9171              "None          6          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9172              "None          8          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9173              "None          9          A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9174              "None          10         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9175              "None          11         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9176              "None          12         D           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9177              "None          13         L           None        N                1.83827367612531                   None                                           1.79015307643158                   None                                            2.2768687598681                  None                                          2.08461171779445                  None                                          2.00120623474388                  None                                          1.92825070277699                  None                                          1.47212860033516                   None                                           1.12978017906854                   None                                           1.20415336139956                   None                                          0.901691390796334                  None                                         0.687390207543568                   None                                          0.455635480573046                  None                                         0.281637123971289                   None                                          0.138259661766539                   None                                       \n", 
9178              "None          14         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9179              "None          15         R           None        N                1.58367544790673                   None                                           1.58127411936947                   None                                           1.61085209029811                  None                                          1.59731540507347                  None                                          1.59237108385522                  None                                          1.58834866344307                  None                                           1.2251048782537                   None                                          0.938142786712004                   None                                           1.03297495592991                   None                                          0.683284686224254                  None                                         0.594447788256641                   None                                          0.383528609383686                  None                                         0.262780814059893                   None                                          0.133469839450564                   None                                       \n", 
9180              "None          16         T           None        N                1.40984232256624                   None                                           1.43947245672073                   None                                           1.10299856647417                  None                                          1.24811470332083                  None                                          1.30521602599932                  None                                          1.35302443831853                  None                                          1.07923777467974                   None                                          0.833345927788896                   None                                          0.934350308974616                   None                                          0.581325254389991                  None                                         0.543659670184793                   None                                          0.346238480454282                  None                                         0.251454336191817                   None                                          0.130436714663781                   None                                       \n", 
9181              "None          17         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9182              "None          18         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9183              "None          19         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9184              "None          21         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9185              "None          24         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9186              "None          25         Q           None        N                1.81569700258844                   None                                           1.77137827615015                   None                                           2.23175875585624                  None                                          2.04612705363098                  None                                           1.9673155780155                  None                                          1.89908711012298                  None                                          1.44829660124856                   None                                           1.11023386429581                   None                                           1.18716091371256                   None                                          0.877306975624962                  None                                         0.677790118853413                   None                                          0.447932002242236                  None                                         0.279785379050945                   None                                          0.137802891887767                   None                                       \n", 
9187              "None          26         Q           None        N                1.61128821168674                   None                                           1.60374392042003                   None                                           1.69619923953765                  None                                          1.65403989292986                  None                                          1.63856717205868                  None                                          1.62595755714564                  None                                          1.24977859227795                   None                                          0.956353494917591                   None                                           1.04972090035774                   None                                          0.702164059520172                  None                                         0.603227813742091                   None                                          0.390116910781037                  None                                         0.264658552037535                   None                                          0.133960994297096                   None                                       \n", 
9188              "None          27         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9189              "None          28         Q           None        N                1.65182797011356                   None                                           1.63676707684161                   None                                           1.81830827892972                  None                                           1.7365089711986                  None                                          1.70601955220877                  None                                          1.68102938663686                  None                                          1.28685736157369                   None                                          0.984047498595701                   None                                            1.0749792109454                   None                                          0.731585685663053                  None                                         0.616577997665602                   None                                          0.400219205533665                  None                                         0.267471993812649                   None                                          0.134690869499646                   None                                       \n", 
9190              "None          29         V           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9191              "None          30         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9192              "None          31         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9193              "None          32         I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9194              "None          33         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9195              "None          34         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9196              "None          35         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9197              "None          36         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9198              "None          38         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9199              "None          39         L           None        N                1.76426439181176                   None                                           1.72885318885161                   None                                           2.11826300085737                  None                                          1.95430201082222                  None                                          1.88794717058464                  None                                          1.83172922971397                  None                                          1.39549951193417                   None                                           1.06783946148624                   None                                           1.14997013232702                   None                                          0.826128785942585                  None                                         0.657105386950171                   None                                          0.431542911580536                  None                                         0.275725736430539                   None                                          0.136791385554619                   None                                       \n", 
9200              "None          40         M           None        N                 1.5521741199158                   None                                           1.55564594516135                   None                                           1.51290906497298                  None                                          1.53245929150759                  None                                          1.53960430408466                  None                                          1.54541832596591                  None                                          1.19750223001929                   None                                          0.917959090226757                   None                                           1.01428385962747                   None                                          0.662779584695967                  None                                         0.584708929219264                   None                                          0.376271266885303                  None                                         0.260671619214194                   None                                          0.132914250767089                   None                                       \n", 
9201              "None          41         A           None        N                1.68339451828261                   None                                           1.66252964414082                   None                                           1.90911961276946                  None                                          1.79959323497326                  None                                          1.75801925517113                  None                                          1.72370710837265                  None                                          1.31646868936419                   None                                           1.00647189763597                   None                                           1.09525348649914                   None                                           0.75605702767542                  None                                         0.627395557358039                   None                                          0.408481831044309                  None                                         0.269716174238842                   None                                          0.135267948387412                   None                                       \n", 
9202              "None          42         A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9203              "None          43         F           None        N                1.58506597154432                   None                                           1.58240542750303                   None                                           1.61517196062351                  None                                          1.60017740004898                  None                                          1.59469990835425                  None                                          1.59024353162528                  None                                          1.22633651794829                   None                                          0.939047922181951                   None                                           1.03380990731605                   None                                          0.684214484755514                  None                                         0.594884298549546                   None                                          0.383855128702894                  None                                         0.262874695048502                   None                                           0.13349447283116                   None                                       \n", 
9204              "None          44         I           None        N                1.57575471961837                   None                                           1.57483015671791                   None                                           1.58622388390755                  None                                          1.58100758841935                  None                                          1.57910319967536                  None                                          1.57755415552211                  None                                          1.21811077066835                   None                                          0.933010299763027                   None                                           1.02823520295828                   None                                           0.67802911457195                  None                                         0.591972285081647                   None                                          0.381678892926696                  None                                         0.262247347241724                   None                                          0.133329708422379                   None                                       \n", 
9205              "None          45         K           None        N                1.77147501495754                   None                                           1.73479633022489                   None                                           2.13509660780385                  None                                          1.96751045408372                  None                                          1.89924480319914                  None                                          1.84124387452692                  None                                          1.40277881643715                   None                                           1.07361367582571                   None                                           1.15506365550891                   None                                          0.832963505534767                  None                                         0.659913187081268                   None                                          0.433751178249555                  None                                         0.276282572106685                   None                                           0.13693095791902                   None                                       \n", 
9206              "None          46         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9207              "None          48         T           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9208              "None          49         A           None        N                2.00297059962685                   None                                           1.92978318052058                   None                                           2.53305709323468                  None                                          2.33052197276846                  None                                          2.22870514722639                  None                                          2.13201782446864                  None                                           1.6587904412969                   None                                           1.29333162369472                   None                                           1.34311052758116                   None                                           1.12559033900783                  None                                         0.770195063841652                   None                                          0.524846264860003                  None                                         0.296857751274362                   None                                          0.141908833673671                   None                                       \n", 
9209              "None          50         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9210              "None          51         Y           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9211              "None          52         V           None        N                1.82421571143794                   None                                           1.77845404105203                   None                                           2.24910726268822                  None                                          2.06078232916932                  None                                          1.98017451806059                  None                                          1.91012195713554                  None                                          1.45724107606646                   None                                           1.11753869321304                   None                                           1.19352234944057                   None                                          0.886361068343012                  None                                         0.681372607920812                   None                                          0.450799407357501                  None                                         0.280478735779163                   None                                          0.137974257665877                   None                                       \n", 
9212              "None          53         A           None        N                2.05019708195234                   None                                           1.97089957318506                   None                                           2.58789168363698                  None                                          2.39027806684801                  None                                          2.28731354878582                  None                                           2.1872118539319                  None                                           1.7165709935896                   None                                           1.34832362477229                   None                                           1.38879751095815                   None                                            1.2085314357749                  None                                         0.799450059125864                   None                                          0.550583841461621                  None                                          0.30195492609136                   None                                          0.143090604877102                   None                                       \n", 
9213              "None          54         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9214              "None          55         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9215              "None          57         G           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9216              "None          58         M           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9217              "None          59         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n" 
9218          ] 
9219          # Check the created theta file. 
9220          lines = theta_file.readlines() 
9221          for i in range(len(lines)): 
9222              # Test lines starting with # 
9223              if theta_result[i][0] == "#": 
9224                  self.assertEqual(theta_result[i], lines[i]) 
9225              # If the line is equal each other, make a line comparison. This should catch lines with None values. 
9226              if theta_result[i] == lines[i]: 
9227                  self.assertEqual(theta_result[i], lines[i]) 
9228              # If the line is not equal each other, make a slower comparison of values. 
9229              else: 
9230                  # Print lines if they don't match. To help find differences. 
9231                  print(theta_result[i]) 
9232                  print(lines[i]) 
9233   
9234                  # First test first 62 characters containing spin information 
9235                  self.assertEqual(theta_result[i][:62], lines[i][:62]) 
9236   
9237                  # Make a string split after 62 characters. Select each second element, so None values are skipped. 
9238                  theta_result_s = theta_result[i][62:].split()[::2] 
9239                  print(theta_result_s ) 
9240                  lines_s = lines[i][62:].split()[::2] 
9241                  print(lines_s) 
9242                  # Loop over the value elements 
9243                  for j in range(len(lines_s)): 
9244                      print(theta_result_s[j], lines_s[j]) 
9245                      # Assume a precision to digits. 
9246                      self.assertAlmostEqual(float(theta_result_s[j]), float(lines_s[j]), 14) 
9247   
9248          # Close file 
9249          theta_file.close() 
9250   
9251          w_eff_file = open(w_eff_filepath, 'r') 
9252          w_eff_result = [ 
9253              "# Parameter description:  Effective field in rotating frame : ( w_eff = sqrt(Omega^2 + w_1^2) ) (rad.s^-1).\n", 
9254              "#\n", 
9255              "# mol_name    res_num    res_name    spin_num    spin_name    r1rho_799.77739910_118.078_1341.110    sd(r1rho_799.77739910_118.078_1341.110)    r1rho_799.77739910_118.078_1648.500    sd(r1rho_799.77739910_118.078_1648.500)    r1rho_799.77739910_118.078_431.000    sd(r1rho_799.77739910_118.078_431.000)    r1rho_799.77739910_118.078_651.200    sd(r1rho_799.77739910_118.078_651.200)    r1rho_799.77739910_118.078_800.500    sd(r1rho_799.77739910_118.078_800.500)    r1rho_799.77739910_118.078_984.000    sd(r1rho_799.77739910_118.078_984.000)    r1rho_799.77739910_124.247_1341.110    sd(r1rho_799.77739910_124.247_1341.110)    r1rho_799.77739910_130.416_1341.110    sd(r1rho_799.77739910_130.416_1341.110)    r1rho_799.77739910_130.416_1648.500    sd(r1rho_799.77739910_130.416_1648.500)    r1rho_799.77739910_130.416_800.500    sd(r1rho_799.77739910_130.416_800.500)    r1rho_799.77739910_142.754_1341.110    sd(r1rho_799.77739910_142.754_1341.110)    r1rho_799.77739910_142.754_800.500    sd(r1rho_799.77739910_142.754_800.500)    r1rho_799.77739910_179.768_1341.110    sd(r1rho_799.77739910_179.768_1341.110)    r1rho_799.77739910_241.459_1341.110    sd(r1rho_799.77739910_241.459_1341.110)    \n", 
9256              "None          5          I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9257              "None          6          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9258              "None          8          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9259              "None          9          A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9260              "None          10         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9261              "None          11         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9262              "None          12         D           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9263              "None          13         L           None        N                8737.12883908829                   None                                           10612.1226552258                   None                                           3558.93734069587                  None                                          4698.27194621826                  None                                          5534.46153956037                  None                                          6599.82570817753                  None                                          8467.62674839481                   None                                           9318.00441649087                   None                                           11095.2662520767                   None                                           6412.33580591254                  None                                          13279.9803044242                   None                                            11430.254637056                  None                                          30318.7268264644                   None                                           61141.1080046448                   None                                       \n", 
9264              "None          14         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9265              "None          15         R           None        N                8427.14155005377                   None                                           10358.3995676635                   None                                           2710.22680763322                  None                                          4093.04942975722                  None                                          5030.86065069262                  None                                          6183.60685459024                  None                                          8956.28403254202                   None                                           10448.6627754369                   None                                           12060.4428066937                   None                                           7966.64282975241                  None                                          15045.8392092364                   None                                           13441.3586252373                  None                                          32438.4764809909                   None                                           63321.5201471181                   None                                       \n", 
9266              "None          16         T           None        N                 8536.7818857229                   None                                            10447.792678989                   None                                           3034.01707453628                  None                                           4314.2767521567                  None                                          5212.43600885913                  None                                          6332.21319855067                  None                                          9558.14311447582                   None                                           11384.2336494604                   None                                           12879.4604966293                   None                                           9159.34604475399                  None                                          16290.1746838959                   None                                           14821.0200530829                  None                                          33866.5933527757                   None                                           64785.3205696403                   None                                       \n", 
9267              "None          17         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9268              "None          18         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9269              "None          19         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9270              "None          21         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9271              "None          24         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9272              "None          25         Q           None        N                8685.60895531182                   None                                           10569.7459677762                   None                                           3430.51272680396                  None                                          4601.75421490393                  None                                          5452.76508815826                  None                                          6531.46859076009                  None                                          8490.06475886501                   None                                           9406.58372902508                   None                                           11169.7602637607                   None                                           6540.38696356753                  None                                          13437.7348017798                   None                                           11613.1632549021                  None                                          30514.0741594726                   None                                           61342.4792156782                   None                                       \n", 
9273              "None          26         Q           None        N                8433.35533683544                   None                                           10363.4554631194                   None                                           2729.48656005151                  None                                          4105.82770792005                  None                                          5041.26238350827                  None                                          6192.07245313098                  None                                          8880.08366342131                   None                                           10312.6868786802                   None                                           11942.8320576165                   None                                           7787.44854491812                  None                                          14853.4987024375                   None                                           13225.7048162038                  None                                          32213.6690023282                   None                                           63090.7407990801                   None                                       \n", 
9274              "None          27         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9275              "None          28         Q           None        N                8454.18308422202                   None                                           10380.4112885894                   None                                           2793.17494362899                  None                                          4148.43953208179                  None                                          5076.02756135055                  None                                          6220.40920270029                  None                                          8777.91538040813                   None                                           10118.8737706315                   None                                           11775.8792998529                   None                                           7528.90766101027                  None                                          14572.4015102398                   None                                            12909.211050939                  None                                          31882.8171856889                   None                                           62750.9120842199                   None                                       \n", 
9276              "None          29         V           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9277              "None          30         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9278              "None          31         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9279              "None          32         I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9280              "None          33         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9281              "None          34         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9282              "None          35         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9283              "None          36         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9284              "None          38         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9285              "None          39         L           None        N                 8586.6405431352                   None                                           10488.5710521378                   None                                           3171.59430904777                  None                                          4412.11227722123                  None                                          5293.69814015286                  None                                          6399.27143075725                  None                                          8557.58926327909                   None                                           9617.45773774313                   None                                           11347.9169998729                   None                                           6840.20010813426                  None                                          13795.1250622375                   None                                           12024.9041436853                  None                                           30951.651485352                   None                                           61793.2130509111                   None                                       \n", 
9286              "None          40         M           None        N                8427.90394711227                   None                                           10359.0198301036                   None                                           2712.59646573568                  None                                          4094.61889210019                  None                                          5032.13762965554                  None                                           6184.6458240746                  None                                          9049.68452800053                   None                                           10607.7913029633                   None                                           12198.5639821231                   None                                           8174.23271685285                  None                                          15266.4924700447                   None                                           13687.9010998756                  None                                          32694.9043143038                   None                                           63584.6371927381                   None                                       \n", 
9287              "None          41         A           None        N                8480.14299737436                   None                                           10401.5648897003                   None                                           2870.79081440785                  None                                          4201.09083283266                  None                                          5119.14733505123                  None                                          6255.64579267482                  None                                          8706.50768957471                   None                                           9972.71017314947                   None                                           11650.5225246067                   None                                           7331.28858930568                  None                                          14354.1616183112                   None                                           12662.3378547029                  None                                          31623.9195264738                   None                                           62484.8290612112                   None                                       \n", 
9288              "None          42         A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9289              "None          43         F           None        N                8427.30062786474                   None                                           10358.5289868368                   None                                            2710.7214015056                  None                                          4093.37694357637                  None                                          5031.12711571215                  None                                          6183.82364721878                  None                                          8952.31975962078                   None                                           10441.7375680915                   None                                           12054.4435931163                   None                                           7957.55789315654                  None                                          15036.1316712316                   None                                           13430.4914212645                  None                                          32427.1596037519                   None                                           63309.9050677925                   None                                       \n", 
9290              "None          44         I           None        N                8426.54623319716                   None                                           10357.9152496503                   None                                            2708.3751705368                  None                                          4091.82359712664                  None                                          5029.86337809029                  None                                          6182.79552045043                  None                                          8979.12144335458                   None                                           10488.2688526334                   None                                           12094.7720286018                   None                                           8018.51779989075                  None                                          15101.1843990883                   None                                           13503.2816173444                  None                                          32502.9389163062                   None                                           63387.6763306952                   None                                       \n", 
9291              "None          45         K           None        N                8599.01176345321                   None                                           10498.7013581079                   None                                           3204.93649737055                  None                                          4436.14046641897                  None                                          5313.74138343704                  None                                          6415.86177652694                  None                                          8546.79665373249                   None                                           9587.16245449134                   None                                           11322.2529042385                   None                                           6797.53838612575                  None                                          13745.1536613763                   None                                           11967.5433300612                  None                                          30890.8603419261                   None                                           61730.6213936947                   None                                       \n", 
9292              "None          46         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9293              "None          48         T           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9294              "None          49         A           None        N                9279.63849130869                   None                                           11063.0654625247                   None                                           4737.11992391463                  None                                          5643.40583860235                  None                                          6356.45614406507                  None                                          7302.87406141381                  None                                          8459.17105047661                   None                                           8761.54554569995                   None                                           10632.2343488142                   None                                           5572.92782399155                  None                                          12102.1714908775                   None                                           10037.6988885228                  None                                          28806.6916858172                   None                                           59579.0348769179                   None                                       \n", 
9295              "None          50         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9296              "None          51         Y           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9297              "None          52         V           None        N                8704.45610117774                   None                                           10585.2389163429                   None                                            3477.9549539207                  None                                          4637.22923167743                  None                                          5482.73656118686                  None                                           6556.5108895527                  None                                          8481.06470969555                   None                                           9372.86414918436                   None                                           11141.3782476763                   None                                           6491.79686536093                  None                                          13378.2843939736                   None                                           11544.3205736882                  None                                            30440.62308788                   None                                           61266.7742546508                   None                                       \n", 
9298              "None          53         A           None        N                9497.02860450276                   None                                           11246.0339326126                   None                                           5149.96766581255                  None                                          5994.15475647208                  None                                          6669.81232845336                  None                                          7577.19152075731                  None                                          8516.77431951689                   None                                           8639.36099840319                   None                                           10531.7750336522                   None                                           5378.79193153767                  None                                          11752.8060152439                   None                                           9613.59939949642                  None                                          28334.9153747994                   None                                           59090.2988815445                   None                                       \n", 
9299              "None          54         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9300              "None          55         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9301              "None          57         G           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9302              "None          58         M           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9303              "None          59         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n" 
9304          ] 
9305          # Check the created w_eff file. 
9306          lines = w_eff_file.readlines() 
9307          for i in range(len(lines)): 
9308              # Test lines starting with # 
9309              if w_eff_result[i][0] == "#": 
9310                  self.assertEqual(w_eff_result[i], lines[i]) 
9311              # If the line is equal each other, make a line comparison. This should catch lines with None values. 
9312              if w_eff_result[i] == lines[i]: 
9313                  self.assertEqual(w_eff_result[i], lines[i]) 
9314              # If the line is not equal each other, make a slower comparison of values. 
9315              else: 
9316                  # Print lines if they don't match. To help find differences. 
9317                  print(w_eff_result[i]) 
9318                  print(lines[i]) 
9319   
9320                  # First test first 62 characters containing spin information 
9321                  self.assertEqual(w_eff_result[i][:62], lines[i][:62]) 
9322   
9323                  # Make a string split after 62 characters. Select each second element, so None values are skipped. 
9324                  w_eff_result_s = w_eff_result[i][62:].split()[::2] 
9325                  print(w_eff_result_s ) 
9326                  lines_s = lines[i][62:].split()[::2] 
9327                  print(lines_s) 
9328                  # Loop over the value elements 
9329                  for j in range(len(lines_s)): 
9330                      print(w_eff_result_s[j], lines_s[j]) 
9331                      # Assume a precision to digits. 
9332                      self.assertAlmostEqual(float(w_eff_result_s[j]), float(lines_s[j]), 14) 
9333   
9334          # Close file 
9335          w_eff_file.close() 
9336   
9337   
9338 -    def verify_estimate_r2eff_err_compare_mc(self): 
9339          """Test the user function for estimating R2eff errors from exponential curve fitting, and compare it with Monte-Carlo simulations. 
9340   
9341          This follows Task 7822. 
9342          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
9343   
9344          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
9345          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
9346          """ 
9347   
9348          # Load the data. 
9349          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep 
9350   
9351          # Set pipe name, bundle and type. 
9352          pipe_name = 'base pipe' 
9353          pipe_bundle = 'relax_disp' 
9354          pipe_type = 'relax_disp' 
9355   
9356          # Create the data pipe. 
9357          self.interpreter.pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type=pipe_type) 
9358   
9359          file = data_path + '1_setup_r1rho_GUI.py' 
9360          self.interpreter.script(file=file, dir=None) 
9361   
9362          # Deselect all spins. 
9363          self.interpreter.deselect.spin(spin_id=':1-100', change_all=False) 
9364   
9365          # Select one spin. 
9366          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
9367   
9368          # Set the model. 
9369          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
9370   
9371          # Check if intensity errors have already been calculated. 
9372          check_intensity_errors() 
9373   
9374          # Do a grid search. 
9375          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=11, constraints=True, verbosity=1) 
9376   
9377          # Set algorithm. 
9378          min_algor = 'Newton' 
9379          constraints = True 
9380          if constraints: 
9381              min_options = ('%s'%(min_algor),) 
9382              #min_algor = 'Log barrier' 
9383              min_algor = 'Method of Multipliers' 
9384              scaling_matrix = assemble_scaling_matrix(scaling=True) 
9385   
9386              # Collect spins 
9387              all_spin_ids = [] 
9388              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9389                  all_spin_ids.append(spin_id) 
9390   
9391              spins = spin_ids_to_containers(all_spin_ids[:1]) 
9392   
9393              # Get constraints 
9394              A, b = linear_constraints(spins=spins, scaling_matrix=scaling_matrix[0]) 
9395          else: 
9396              min_options = () 
9397              A, b = None, None 
9398          min_options = () 
9399          sim_boot = 200 
9400          scaling_list = [1.0, 1.0] 
9401   
9402          # Minimise. 
9403          self.interpreter.minimise.execute(min_algor=min_algor, constraints=constraints, verbosity=1) 
9404   
9405          # Loop over old err attributes. 
9406          err_attr_list = ['r2eff_err', 'i0_err'] 
9407   
9408          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9409              # Loop over old err attributes. 
9410              for err_attr in err_attr_list: 
9411                  if hasattr(cur_spin, err_attr): 
9412                      delattr(cur_spin, err_attr) 
9413   
9414          # Collect the estimation data from boot. 
9415          my_dic = {} 
9416          param_key_list = [] 
9417          est_keys = [] 
9418          est_key = '-2' 
9419          est_keys.append(est_key) 
9420          spin_id_list = [] 
9421   
9422          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9423              # Add key to dic. 
9424              my_dic[spin_id] = {} 
9425   
9426              # Add key for estimate. 
9427              my_dic[spin_id][est_key] = {} 
9428   
9429              # Add spin key to list. 
9430              spin_id_list.append(spin_id) 
9431   
9432              # Generate spin string. 
9433              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9434   
9435              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
9436                  # Generate the param_key. 
9437                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
9438   
9439                  # Append key. 
9440                  param_key_list.append(param_key) 
9441   
9442                  # Add key to dic. 
9443                  my_dic[spin_id][est_key][param_key] = {} 
9444   
9445                  values = [] 
9446                  errors = [] 
9447                  times = [] 
9448                  for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
9449                      values.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)) 
9450                      errors.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)) 
9451                      times.append(time) 
9452   
9453                  # Convert to numpy array. 
9454                  values = asarray(values) 
9455                  errors = asarray(errors) 
9456                  times = asarray(times) 
9457   
9458                  r2eff = getattr(cur_spin, 'r2eff')[param_key] 
9459                  i0 = getattr(cur_spin, 'i0')[param_key] 
9460   
9461                  R_m_sim_l = [] 
9462                  I0_m_sim_l = [] 
9463                  for j in range(sim_boot): 
9464                      if j in range(0, 100000, 100): 
9465                          print("Simulation %i"%j) 
9466                      # Start minimisation. 
9467   
9468                      # Produce errors 
9469                      I_err = [] 
9470                      for j, error in enumerate(errors): 
9471                          I_error = gauss(values[j], error) 
9472                          I_err.append(I_error) 
9473                      # Convert to numpy array. 
9474                      I_err = asarray(I_err) 
9475   
9476                      x0 = [r2eff, i0] 
9477                      model = Relax_fit_opt(num_params=len(x0), values=I_err, errors=errors, relax_times=times, scaling_matrix=scaling_list) 
9478   
9479                      # Ref input. 
9480                      #def generic_minimise(func=None, dfunc=None, d2func=None, args=(), x0=None, min_algor=None, min_options=None, func_tol=1e-25, grad_tol=None, maxiter=1e6, A=None, b=None, l=None, u=None, c=None, dc=None, d2c=None, print_flag=0, print_prefix="", full_output=False): 
9481                      # l=l, u=u, c=c, dc=dc, d2c=d2c 
9482                      # l: Lower bound constraint vector (l <= x <= u). 
9483                      # u: Upper bound constraint vector (l <= x <= u). 
9484                      # c: User supplied constraint function. 
9485                      # dc: User supplied constraint gradient function. 
9486                      params_minfx_sim_j, chi2_minfx_sim_j, iter_count, f_count, g_count, h_count, warning = generic_minimise(func=model.func, dfunc=model.dfunc, d2func=model.d2func, args=(), x0=x0, min_algor=min_algor, min_options=min_options, A=A, b=b, full_output=True, print_flag=0) 
9487   
9488                      R_m_sim_j, I0_m_sim_j = params_minfx_sim_j 
9489                      R_m_sim_l.append(R_m_sim_j) 
9490                      I0_m_sim_l.append(I0_m_sim_j) 
9491   
9492                  # Get stats on distribution. 
9493                  sigma_R_sim = std(asarray(R_m_sim_l), ddof=1) 
9494                  sigma_I0_sim = std(asarray(I0_m_sim_l), ddof=1) 
9495                  my_dic[spin_id][est_key][param_key]['r2eff_err'] = sigma_R_sim 
9496                  my_dic[spin_id][est_key][param_key]['i0_err'] = sigma_I0_sim 
9497   
9498          # Estimate R2eff errors. 
9499          self.interpreter.relax_disp.r2eff_err_estimate() 
9500   
9501          est_key = '-1' 
9502          est_keys.append(est_key) 
9503   
9504          # Collect data. 
9505          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9506              # Add key for estimate. 
9507              my_dic[spin_id][est_key] = {} 
9508   
9509              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
9510                  # Generate the param_key. 
9511                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
9512   
9513                  # Add key to dic. 
9514                  my_dic[spin_id][est_key][param_key] = {} 
9515   
9516                  # Get the value. 
9517                  # Loop over err attributes. 
9518                  for err_attr in err_attr_list: 
9519                      if hasattr(cur_spin, err_attr): 
9520                          get_err_attr = getattr(cur_spin, err_attr)[param_key] 
9521                      else: 
9522                          get_err_attr = 0.0 
9523   
9524                      # Save to dic. 
9525                      my_dic[spin_id][est_key][param_key][err_attr] = get_err_attr 
9526   
9527   
9528          # Make Carlo Simulations number 
9529          mc_number_list = list(range(0, 1000, 250)) 
9530   
9531          sim_attr_list = ['chi2_sim', 'f_count_sim', 'g_count_sim', 'h_count_sim', 'i0_sim', 'iter_sim', 'peak_intensity_sim', 'r2eff_sim', 'select_sim', 'warning_sim'] 
9532   
9533          # Loop over the Monte Carlo simulations: 
9534          for number in mc_number_list: 
9535              # First delete old simulations. 
9536              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9537                  # Loop over old err attributes. 
9538                  for err_attr in err_attr_list: 
9539                      if hasattr(cur_spin, err_attr): 
9540                          delattr(cur_spin, err_attr) 
9541   
9542                  # Loop over the simulated attributes. 
9543                  for sim_attr in sim_attr_list: 
9544                      if hasattr(cur_spin, sim_attr): 
9545                          delattr(cur_spin, sim_attr) 
9546   
9547              self.interpreter.monte_carlo.setup(number=number) 
9548              self.interpreter.monte_carlo.create_data() 
9549              self.interpreter.monte_carlo.initial_values() 
9550              self.interpreter.minimise.execute(min_algor=min_algor, constraints=constraints) 
9551              self.interpreter.eliminate() 
9552              self.interpreter.monte_carlo.error_analysis() 
9553   
9554              est_key = '%i'%number 
9555              est_keys.append(est_key) 
9556   
9557              # Collect data. 
9558              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9559                  # Add key for estimate. 
9560                  my_dic[spin_id][est_key] = {} 
9561   
9562                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
9563                      # Generate the param_key. 
9564                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
9565   
9566                      # Add key to dic. 
9567                      my_dic[spin_id][est_key][param_key] = {} 
9568   
9569                      # Get the value. 
9570                      # Loop over err attributes. 
9571                      for err_attr in err_attr_list: 
9572                          if hasattr(cur_spin, err_attr): 
9573                              get_err_attr = getattr(cur_spin, err_attr)[param_key] 
9574                          else: 
9575                              get_err_attr = 0.0 
9576   
9577                          # Save to dic. 
9578                          my_dic[spin_id][est_key][param_key][err_attr] = get_err_attr 
9579   
9580          # Set what to extract. 
9581          err_attr = err_attr_list[0] 
9582   
9583          # Define list with text. 
9584          text_list = [] 
9585   
9586          # Now loop through the data. 
9587          for spin_id in spin_id_list: 
9588              for est_key in est_keys: 
9589                  # Define list to pickup data. 
9590                  r2eff_err_list = [] 
9591   
9592                  for param_key in param_key_list: 
9593                      # Get the value. 
9594                      r2eff_err = my_dic[spin_id][est_key][param_key][err_attr] 
9595   
9596                      # Add to list. 
9597                      r2eff_err_list.append(r2eff_err) 
9598   
9599                  # Sum the list 
9600                  sum_array = sum(array(r2eff_err_list)) 
9601   
9602                  # Join floats to string. 
9603                  r2eff_err_str = " ".join(format(x, "2.3f") for x in r2eff_err_list) 
9604   
9605                  # Define print string. 
9606                  text = "%8s %s sum= %2.3f" % (est_key, r2eff_err_str, sum_array) 
9607                  text_list.append(text) 
9608   
9609   
9610          # Now print. 
9611          filepath = NamedTemporaryFile(delete=False).name 
9612          # Open the files for testing. 
9613          w_file = open(filepath, 'w') 
9614   
9615          print("Printing the estimated R2eff error as function of estimation from Co-variance and number of Monte-Carlo simulations.") 
9616   
9617          for text in text_list: 
9618              # Print. 
9619              print(text) 
9620   
9621              # Write to file. 
9622              w_file.write(text+"\n") 
9623   
9624          # Close files 
9625          w_file.close() 
9626   
9627          print("Filepath is: %s"%filepath) 
9628          print("Start 'gnuplot' and write:") 
9629          print("set term dumb") 
9630          print("plot '%s' using 1:17 title 'R2eff error as function of MC number' w linespoints "%filepath) 
9631   
9632   
9633 -    def verify_r1rho_kjaergaard_missing_r1(self, models=None, result_dir_name=None, r2eff_estimate=None): 
9634          """Verification of test_r1rho_kjaergaard_missing_r1.""" 
9635   
9636          # Check the kex value of residue 52 
9637          #self.assertAlmostEqual(cdp.mol[0].res[41].spin[0].kex, ds.ref[':52@N'][6]) 
9638   
9639          # Print results for each model. 
9640          print("\n\n################") 
9641          print("Printing results") 
9642          print("################\n") 
9643          for model in models: 
9644              # Skip R2eff model. 
9645              if model == MODEL_R2EFF: 
9646                  continue 
9647   
9648              # Switch to pipe. 
9649              self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
9650              print("\nModel: %s" % (model)) 
9651   
9652              # Loop over the spins. 
9653              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9654                  # Generate spin string. 
9655                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9656   
9657                  # Loop over the parameters. 
9658                  print("Optimised parameters for spin: %s" % (spin_string)) 
9659                  for param in cur_spin.params + ['chi2']: 
9660                      # Get the value. 
9661                      if param in ['r1', 'r2']: 
9662                          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
9663                              # Generate the R20 key. 
9664                              r20_key = generate_r20_key(exp_type=exp_type, frq=frq) 
9665   
9666                              # Get the value. 
9667                              value = getattr(cur_spin, param)[r20_key] 
9668   
9669                              # Print value. 
9670                              print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value)) 
9671   
9672                              # Compare values. 
9673                              if spin_id == ':52@N': 
9674                                  if param == 'r1': 
9675                                      if model == MODEL_NOREX: 
9676                                          if r2eff_estimate == 'direct': 
9677                                              self.assertAlmostEqual(value, 1.46138805) 
9678                                          elif r2eff_estimate == 'MC2000': 
9679                                              self.assertAlmostEqual(value, 1.46328102) 
9680                                          elif r2eff_estimate == 'chi2_pyt': 
9681                                              self.assertAlmostEqual(value, 1.43820629) 
9682                                      elif model == MODEL_DPL94: 
9683                                          if r2eff_estimate == 'direct': 
9684                                              self.assertAlmostEqual(value, 1.44845742) 
9685                                          elif r2eff_estimate == 'MC2000': 
9686                                              self.assertAlmostEqual(value, 1.45019848) 
9687                                          elif r2eff_estimate == 'chi2_pyt': 
9688                                              self.assertAlmostEqual(value, 1.44666512) 
9689                                      elif model == MODEL_TP02: 
9690                                          if r2eff_estimate == 'direct': 
9691                                              self.assertAlmostEqual(value, 1.54354392) 
9692                                          elif r2eff_estimate == 'MC2000': 
9693                                              self.assertAlmostEqual(value, 1.54352369) 
9694                                          elif r2eff_estimate == 'chi2_pyt': 
9695                                              self.assertAlmostEqual(value, 1.55964020) 
9696                                      elif model == MODEL_TAP03: 
9697                                          if r2eff_estimate == 'direct': 
9698                                              self.assertAlmostEqual(value, 1.54356410) 
9699                                          elif r2eff_estimate == 'MC2000': 
9700                                              self.assertAlmostEqual(value, 1.54354367) 
9701                                          elif r2eff_estimate == 'chi2_pyt': 
9702                                              self.assertAlmostEqual(value, 1.55967157) 
9703                                      elif model == MODEL_MP05: 
9704                                          if r2eff_estimate == 'direct': 
9705                                              self.assertAlmostEqual(value, 1.54356416) 
9706                                          elif r2eff_estimate == 'MC2000': 
9707                                              self.assertAlmostEqual(value, 1.54354372) 
9708                                          elif r2eff_estimate == 'chi2_pyt': 
9709                                              self.assertAlmostEqual(value, 1.55967163) 
9710                                      elif model == MODEL_NS_R1RHO_2SITE: 
9711                                          if r2eff_estimate == 'direct': 
9712                                              self.assertAlmostEqual(value, 1.41359221, 5) 
9713                                          elif r2eff_estimate == 'MC2000': 
9714                                              self.assertAlmostEqual(value, 1.41321968, 5) 
9715                                          elif r2eff_estimate == 'chi2_pyt': 
9716                                              self.assertAlmostEqual(value, 1.36303129, 5) 
9717   
9718                                  elif param == 'r2': 
9719                                      if model == MODEL_NOREX: 
9720                                          if r2eff_estimate == 'direct': 
9721                                              self.assertAlmostEqual(value, 11.48392439) 
9722                                          elif r2eff_estimate == 'MC2000': 
9723                                              self.assertAlmostEqual(value, 11.48040934) 
9724                                          elif r2eff_estimate == 'chi2_pyt': 
9725                                              self.assertAlmostEqual(value, 11.47224488) 
9726                                      elif model == MODEL_DPL94: 
9727                                          if r2eff_estimate == 'direct': 
9728                                              self.assertAlmostEqual(value, 10.15688372, 6) 
9729                                          elif r2eff_estimate == 'MC2000': 
9730                                              self.assertAlmostEqual(value, 10.16304887, 6) 
9731                                          elif r2eff_estimate == 'chi2_pyt': 
9732                                              self.assertAlmostEqual(value, 9.20037797, 6) 
9733                                      elif model == MODEL_TP02: 
9734                                          if r2eff_estimate == 'direct': 
9735                                              self.assertAlmostEqual(value, 9.72654896, 6) 
9736                                          elif r2eff_estimate == 'MC2000': 
9737                                              self.assertAlmostEqual(value, 9.72772726, 6) 
9738                                          elif r2eff_estimate == 'chi2_pyt': 
9739                                              self.assertAlmostEqual(value, 9.53948340, 6) 
9740                                      elif model == MODEL_TAP03: 
9741                                          if r2eff_estimate == 'direct': 
9742                                              self.assertAlmostEqual(value, 9.72641887, 6) 
9743                                          elif r2eff_estimate == 'MC2000': 
9744                                              self.assertAlmostEqual(value, 9.72759374, 6) 
9745                                          elif r2eff_estimate == 'chi2_pyt': 
9746                                              self.assertAlmostEqual(value, 9.53926913, 6) 
9747                                      elif model == MODEL_MP05: 
9748                                          if r2eff_estimate == 'direct': 
9749                                              self.assertAlmostEqual(value, 9.72641723, 6) 
9750                                          elif r2eff_estimate == 'MC2000': 
9751                                              self.assertAlmostEqual(value, 9.72759220, 6) 
9752                                          elif r2eff_estimate == 'chi2_pyt': 
9753                                              self.assertAlmostEqual(value, 9.53926778, 6) 
9754                                      elif model == MODEL_NS_R1RHO_2SITE: 
9755                                          if r2eff_estimate == 'direct': 
9756                                              self.assertAlmostEqual(value, 9.34531535, 5) 
9757                                          elif r2eff_estimate == 'MC2000': 
9758                                              self.assertAlmostEqual(value, 9.34602793, 5) 
9759                                          elif r2eff_estimate == 'chi2_pyt': 
9760                                              self.assertAlmostEqual(value, 9.17631409, 5) 
9761   
9762                      # For all other parameters. 
9763                      else: 
9764                          # Get the value. 
9765                          value = getattr(cur_spin, param) 
9766   
9767                          # Print value. 
9768                          print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value)) 
9769   
9770                          # Compare values. 
9771                          if spin_id == ':52@N': 
9772                              if param == 'phi_ex': 
9773                                  if model == MODEL_DPL94: 
9774                                      if r2eff_estimate == 'direct': 
9775                                          self.assertAlmostEqual(value, 0.07599563) 
9776                                      elif r2eff_estimate == 'MC2000': 
9777                                          self.assertAlmostEqual(value, 0.07561937) 
9778                                      elif r2eff_estimate == 'chi2_pyt': 
9779                                          self.assertAlmostEqual(value, 0.12946061) 
9780   
9781                              elif param == 'pA': 
9782                                  if model == MODEL_TP02: 
9783                                      if r2eff_estimate == 'direct': 
9784                                          self.assertAlmostEqual(value, 0.88827040) 
9785                                      elif r2eff_estimate == 'MC2000': 
9786                                          self.assertAlmostEqual(value, 0.88807487) 
9787                                      elif r2eff_estimate == 'chi2_pyt': 
9788                                          self.assertAlmostEqual(value, 0.87746233) 
9789                                  elif model == MODEL_TAP03: 
9790                                      if r2eff_estimate == 'direct': 
9791                                          self.assertAlmostEqual(value, 0.88828922) 
9792                                      elif r2eff_estimate == 'MC2000': 
9793                                          self.assertAlmostEqual(value, 0.88809318) 
9794                                      elif r2eff_estimate == 'chi2_pyt': 
9795                                          self.assertAlmostEqual(value, 0.87747558) 
9796                                  elif model == MODEL_MP05: 
9797                                      if r2eff_estimate == 'direct': 
9798                                          self.assertAlmostEqual(value, 0.88828924, 6) 
9799                                      elif r2eff_estimate == 'MC2000': 
9800                                          self.assertAlmostEqual(value, 0.88809321) 
9801                                      elif r2eff_estimate == 'chi2_pyt': 
9802                                          self.assertAlmostEqual(value, 0.87747562) 
9803                                  elif model == MODEL_NS_R1RHO_2SITE: 
9804                                      if r2eff_estimate == 'direct': 
9805                                          self.assertAlmostEqual(value, 0.94504369, 6) 
9806                                      elif r2eff_estimate == 'MC2000': 
9807                                          self.assertAlmostEqual(value, 0.94496541, 6) 
9808                                      elif r2eff_estimate == 'chi2_pyt': 
9809                                          self.assertAlmostEqual(value, 0.92084707, 6) 
9810   
9811                              elif param == 'dw': 
9812                                  if model == MODEL_TP02: 
9813                                      if r2eff_estimate == 'direct': 
9814                                          self.assertAlmostEqual(value, 1.08875840, 6) 
9815                                      elif r2eff_estimate == 'MC2000': 
9816                                          self.assertAlmostEqual(value, 1.08765638, 6) 
9817                                      elif r2eff_estimate == 'chi2_pyt': 
9818                                          self.assertAlmostEqual(value, 1.09753230, 6) 
9819                                  elif model == MODEL_TAP03: 
9820                                      if r2eff_estimate == 'direct': 
9821                                          self.assertAlmostEqual(value, 1.08837238, 6) 
9822                                      elif r2eff_estimate == 'MC2000': 
9823                                          self.assertAlmostEqual(value, 1.08726698, 6) 
9824                                      elif r2eff_estimate == 'chi2_pyt': 
9825                                          self.assertAlmostEqual(value, 1.09708821, 6) 
9826                                  elif model == MODEL_MP05: 
9827                                      if r2eff_estimate == 'direct': 
9828                                          self.assertAlmostEqual(value, 1.08837241, 6) 
9829                                      elif r2eff_estimate == 'MC2000': 
9830                                          self.assertAlmostEqual(value, 1.08726706, 6) 
9831                                      elif r2eff_estimate == 'chi2_pyt': 
9832                                          self.assertAlmostEqual(value, 1.09708832, 6) 
9833                                  elif model == MODEL_NS_R1RHO_2SITE: 
9834                                      if r2eff_estimate == 'direct': 
9835                                          self.assertAlmostEqual(value, 1.56001812, 5) 
9836                                      elif r2eff_estimate == 'MC2000': 
9837                                          self.assertAlmostEqual(value, 1.55833321, 5) 
9838                                      elif r2eff_estimate == 'chi2_pyt': 
9839                                          self.assertAlmostEqual(value, 1.36406712, 5) 
9840   
9841                              elif param == 'kex': 
9842                                  if model == MODEL_DPL94: 
9843                                      if r2eff_estimate == 'direct': 
9844                                          self.assertAlmostEqual(value/1e5, 4460.43711569/1e5, 7) 
9845                                      elif r2eff_estimate == 'MC2000': 
9846                                          self.assertAlmostEqual(value/1e5, 4419.03917195/1e5, 7) 
9847                                      elif r2eff_estimate == 'chi2_pyt': 
9848                                          self.assertAlmostEqual(value/1e5, 6790.22736344/1e5, 7) 
9849                                  elif model == MODEL_TP02: 
9850                                      if r2eff_estimate == 'direct': 
9851                                          self.assertAlmostEqual(value/1e5, 4921.28602757/1e5, 7) 
9852                                      elif r2eff_estimate == 'MC2000': 
9853                                          self.assertAlmostEqual(value/1e5, 4904.70144883/1e5, 7) 
9854                                      elif r2eff_estimate == 'chi2_pyt': 
9855                                          self.assertAlmostEqual(value/1e5, 5146.20306591/1e5, 7) 
9856                                  elif model == MODEL_TAP03: 
9857                                      if r2eff_estimate == 'direct': 
9858                                          self.assertAlmostEqual(value/1e5, 4926.42963491/1e5, 7) 
9859                                      elif r2eff_estimate == 'MC2000': 
9860                                          self.assertAlmostEqual(value/1e5, 4909.86877150/1e5, 7) 
9861                                      elif r2eff_estimate == 'chi2_pyt': 
9862                                          self.assertAlmostEqual(value/1e5, 5152.51105814/1e5, 7) 
9863                                  elif model == MODEL_MP05: 
9864                                      if r2eff_estimate == 'direct': 
9865                                          self.assertAlmostEqual(value/1e5, 4926.44236315/1e5, 7) 
9866                                      elif r2eff_estimate == 'MC2000': 
9867                                          self.assertAlmostEqual(value/1e5, 4909.88110195/1e5, 7) 
9868                                      elif r2eff_estimate == 'chi2_pyt': 
9869                                          self.assertAlmostEqual(value/1e5, 5152.52097111/1e5, 7) 
9870                                  elif model == MODEL_NS_R1RHO_2SITE: 
9871                                      if r2eff_estimate == 'direct': 
9872                                          self.assertAlmostEqual(value/1e5, 5628.66061488/1e5, 6) 
9873                                      elif r2eff_estimate == 'MC2000': 
9874                                          self.assertAlmostEqual(value/1e5, 5610.20221435/1e5, 6) 
9875                                      elif r2eff_estimate == 'chi2_pyt': 
9876                                          self.assertAlmostEqual(value/1e5, 5643.34067090/1e5, 6) 
9877   
9878                              elif param == 'chi2': 
9879                                  if model == MODEL_NOREX: 
9880                                      if r2eff_estimate == 'direct': 
9881                                          self.assertAlmostEqual(value, 848.42016907, 5) 
9882                                      elif r2eff_estimate == 'MC2000': 
9883                                          self.assertAlmostEqual(value, 3363.95829122, 5) 
9884                                      elif r2eff_estimate == 'chi2_pyt': 
9885                                          self.assertAlmostEqual(value, 5976.49946726, 5) 
9886                                  elif model == MODEL_DPL94: 
9887                                      if r2eff_estimate == 'direct': 
9888                                          self.assertAlmostEqual(value, 179.47041241) 
9889                                      elif r2eff_estimate == 'MC2000': 
9890                                          self.assertAlmostEqual(value, 710.24767560) 
9891                                      elif r2eff_estimate == 'chi2_pyt': 
9892                                          self.assertAlmostEqual(value, 612.72616697, 5) 
9893                                  elif model == MODEL_TP02: 
9894                                      if r2eff_estimate == 'direct': 
9895                                          self.assertAlmostEqual(value, 29.33882530, 6) 
9896                                      elif r2eff_estimate == 'MC2000': 
9897                                          self.assertAlmostEqual(value, 114.47142772, 6) 
9898                                      elif r2eff_estimate == 'chi2_pyt': 
9899                                          self.assertAlmostEqual(value, 250.50838162, 5) 
9900                                  elif model == MODEL_TAP03: 
9901                                      if r2eff_estimate == 'direct': 
9902                                          self.assertAlmostEqual(value, 29.29050673, 6) 
9903                                      elif r2eff_estimate == 'MC2000': 
9904                                          self.assertAlmostEqual(value, 114.27987534) 
9905                                      elif r2eff_estimate == 'chi2_pyt': 
9906                                          self.assertAlmostEqual(value, 250.04050719, 5) 
9907                                  elif model == MODEL_MP05: 
9908                                      if r2eff_estimate == 'direct': 
9909                                          self.assertAlmostEqual(value, 29.29054301, 6) 
9910                                      elif r2eff_estimate == 'MC2000': 
9911                                          self.assertAlmostEqual(value, 114.28002272) 
9912                                      elif r2eff_estimate == 'chi2_pyt': 
9913                                          self.assertAlmostEqual(value, 250.04077478, 5) 
9914                                  elif model == MODEL_NS_R1RHO_2SITE: 
9915                                      if r2eff_estimate == 'direct': 
9916                                          self.assertAlmostEqual(value, 34.44010543, 6) 
9917                                      elif r2eff_estimate == 'MC2000': 
9918                                          self.assertAlmostEqual(value, 134.14368365) 
9919                                      elif r2eff_estimate == 'chi2_pyt': 
9920                                          self.assertAlmostEqual(value, 278.55121388, 5) 
9921   
9922   
9923          # Print the final pipe. 
9924          model = 'final' 
9925          self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
9926          print("\nFinal pipe") 
9927   
9928          # Loop over the spins. 
9929          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9930              # Generate spin string. 
9931              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9932   
9933              # Loop over the parameters. 
9934              print("Optimised model for spin: %s" % (spin_string)) 
9935              param = 'model' 
9936   
9937              # Get the value. 
9938              value = getattr(cur_spin, param) 
9939              print("%-10s %-6s %-6s %6s" % ("Parameter:", param, "Value:", value)) 
9940   
9941   
9942          ### Now check some of the written out files. 
9943          file_names = ['r1rho_prime', 'r1'] 
9944   
9945          for file_name_i in file_names: 
9946   
9947              # Make the file name. 
9948              file_name = "%s.out" % file_name_i 
9949   
9950              # Get the file path. 
9951              file_path = get_file_path(file_name, result_dir_name + sep + model) 
9952   
9953              # Test the file exists. 
9954              print("Testing file access to: %s"%file_path) 
9955              self.assert_(access(file_path, F_OK)) 
9956   
9957              # Now open, and compare content, line by line. 
9958              file_prod = open(file_path) 
9959              lines_prod = file_prod.readlines() 
9960              file_prod.close() 
9961   
9962              # Loop over the lines. 
9963              for i, line in enumerate(lines_prod): 
9964                  # Make the string test 
9965                  line_split = line.split() 
9966   
9967                  # Continue for comment lines. 
9968                  if line_split[0] == "#": 
9969                      print(line), 
9970                      continue 
9971   
9972                  # Assign the split of the line. 
9973                  mol_name, res_num, res_name, spin_num, spin_name, val, sd_error = line_split 
9974                  print(mol_name, res_num, res_name, spin_num, spin_name, val, sd_error) 
9975   
9976                  if res_num == '52': 
9977                      # Assert that the value is not None. 
9978                      self.assertNotEqual(val, 'None') 
9979